Research questions

The primary goal of this study was a comparison of grab sample, stomach tubing and feces to understand how different sampling methods will effect the microbial communities found in samples. The current “gold standard” for surveying the rumen microbiome is with a grab sample from the rument that contains both liquid and solid particles. On a commercial dairy, fecal sampling is easy to do. Stomach tube could be done with a little more time. If a fecal sample is not representative of the stomach tube, then there is no sense doing the fecal sampling as a monitor for rumen conditions. In reality, if the stomach tube and the fecal sample do not reflect the grab sample (gold standard) then neither would be used to monitor rumen microbial health (populations).

We seek to answer the following questions:

How are sample types different?
- Alpha diversity (richness and evenness)
- Beta diversity
- Differentially abundant and differentially variable ASVs.
What ASVs are shared between samples of the same type.

A secondary question is the decomposition of the grab sample (liquid strained & solid). The grab sample was separated into liquid strained and solid particulate by pressing the grab sample through cheese cloth to get liquid strained and solid particulate. We will have a closer look at what communites are in what parts of the grab sample.

Running DADA2 to get ASVs and assign taxonomy.

This program infers exact amplicon sequence variants (ASVs) from amplicon data, resolving biological differences of even 1 or 2 nucleotides. This algorithum is prefered as DADA2 reports fewer false positive sequence variants than other methods report false OTUs. Note that this is a computationally expensive so its run on a cluster and then the R objects are read in.

First we will read in the data and trim ends where there is poor quality.

The next steps learn the error rates of the data and identifies unique sequences. These data are fed into the main dada2 algorithum that makes a table of ASVs. Reads are merged and chimerias removed prior to making the final ASV table. Taxaonomy was assined using the silva database.

Getting information out of DADA2 Objects.

Let’s check the sizes of the sequences as a way to determine contamination.

## 
##  221  223  226  227  229  230  231  232  237  246  251  252  253  254  255 
##    1    1    2    1    3    8    1    1    2    1    5  858 4510  131    6 
##  256  257  263  269  270  271  275  277  281  283  285  287  292  293  294 
##    1    1    2    7   24    2    1    1    1    1   12    1    7   26    1 
##  342  383 
##    1    1

## [1] 256.5

These sequences have a median length of 256.5 with most are less than 390bp. The sequences longer sequences may be the result of non-specific priming. We will look at this again after specific and thoughtful filtering. If long sequences remain after filtering we will look at them closer to make sure they are infact from bacterial origin.

Now we check the number of chimeras in the dataset.

## [1] 0.9795362

Here we see that 2.01% of the sequences were identified to be chimerias and were removed from the dataset. Next, we will have a look at the read stats.

##                            input filtered denoisedF denoisedR merged
## 282_Trim_R1.fastq.gz        9052     7645      7522      7410   6879
## 283_Trim_R1.fastq.gz       13464    11359     11216     11089  10503
## 284_Trim_R1.fastq.gz        9144     7769      7658      7584   7108
## 285_Trim_R1.fastq.gz        9372     7985      7856      7727   7211
## 286_Trim_R1.fastq.gz       11633     9828      9692      9605   9020
## 287_Trim_R1.fastq.gz        9598     8197      8048      7949   7420
## 288_Trim_R1.fastq.gz        5220     4431      4354      4290   4019
## 289_Trim_R1.fastq.gz        5475     4643      4578      4501   4235
## 290_Trim_R1.fastq.gz       11958    10168     10032      9968   9301
## 291_Trim_R1.fastq.gz        5232     4445      4382      4330   4063
## 292_Trim_R1.fastq.gz        9222     7816      7700      7586   7048
## 293_Trim_R1.fastq.gz        8496     7327      7225      7160   6789
## 294_Trim_R1.fastq.gz        5616     4744      4664      4594   4331
## 295_Trim_R1.fastq.gz        7305     6196      6095      6008   5601
## 296_Trim_R1.fastq.gz        8684     7346      7247      7115   6652
## 297_Trim_R1.fastq.gz        7593     6304      6213      6078   5683
## 298_Trim_R1.fastq.gz       11098     9374      9213      9087   8521
## 299_Trim_R1.fastq.gz        9184     7836      7704      7577   7100
## 300_Trim_R1.fastq.gz        8612     7226      7115      6969   6516
## 301_Trim_R1.fastq.gz        7719     6476      6345      6231   5827
## 302_Trim_R1.fastq.gz        6805     5725      5634      5572   5198
## 303_Trim_R1.fastq.gz        7157     6103      6008      5894   5509
## 304_Trim_R1.fastq.gz        9437     8116      7823      7844   6943
## 306_Trim_R1.fastq.gz        8613     7475      7359      7312   6933
## 307_Trim_R1.fastq.gz        5220     4588      4514      4482   4260
## 308_Trim_R1.fastq.gz        9229     7774      7643      7623   7145
## 309_Trim_R1.fastq.gz       12202    10326     10125     10016   9420
## 310_Trim_R1.fastq.gz        9933     8518      8388      8336   7893
## 311_Trim_R1.fastq.gz       13931    11779     11565     11480  10846
## 312_Trim_R1.fastq.gz        7955     6758      6643      6604   6191
## 314_Trim_R1.fastq.gz        6183     5271      5196      5116   4731
## 359_Trim_R1.fastq.gz       11088     9360      9236      9153   8597
## 360_Trim_R1.fastq.gz       11846    10163      9985      9881   9254
## 361_Trim_R1.fastq.gz       13308    11306     11124     11004  10307
## 362_Trim_R1.fastq.gz        9383     7936      7805      7761   7266
## 363_Trim_R1.fastq.gz        6851     5715      5612      5538   5182
## 365_Trim_R1.fastq.gz        6992     5982      5890      5824   5480
## 366_Trim_R1.fastq.gz        6330     5713      5597      5572   5234
## 367_Trim_R1.fastq.gz        6732     6075      5956      5948   5526
## 368_Trim_R1.fastq.gz        8080     7280      7123      7112   6699
## 369_Trim_R1.fastq.gz       16363    14678     14369     14329  13337
## 370_Trim_R1.fastq.gz       11504    10371     10027     10134   9326
## 371_Trim_R1.fastq.gz       11769    10494     10253     10253   9557
## 372_Trim_R1.fastq.gz       15193    13658     13372     13357  12485
## 373_Trim_R1.fastq.gz       14512    13010     12743     12711  11860
## 374_Trim_R1.fastq.gz       11580    10359     10154     10090   9456
## 375_Trim_R1.fastq.gz       12296    11085     10797     10768   9966
## 376_Trim_R1.fastq.gz       13002    11778     11529     11506  10744
## 378_Trim_R1.fastq.gz       13050    11829     11566     11509  10739
## 379_Trim_R1.fastq.gz       13484    11184     11022     10760   9935
## 380_Trim_R1.fastq.gz       12795    10698     10534     10299   9511
## 381_Trim_R1.fastq.gz       13125    11040     10841     10659   9902
## 382_Trim_R1.fastq.gz       21991    18506     18264     17908  16698
## 383_Trim_R1.fastq.gz        8923     7465      7362      7233   6745
## 384_Trim_R1.fastq.gz       12080    10234     10064      9874   9117
## 385_Trim_R1.fastq.gz        9747     8208      8072      7933   7441
## 386_Trim_R1.fastq.gz       16271    13550     13287     13095  12188
## 387_Trim_R1.fastq.gz       25059    21471     20099     19119  15561
## 388_Trim_R1.fastq.gz       13699    11576     11356     11247  10419
## 389_Trim_R1.fastq.gz       14755    12555     12069     12082  10761
## 390_Trim_R1.fastq.gz        2836     2461      2427      2377   2227
## 505_Trim_R1.fastq.gz        6303     5333      5231      5210   4914
## 506_Trim_R1.fastq.gz       10828     9075      8896      8819   8260
## 507_Trim_R1.fastq.gz        7388     6304      6214      6180   5849
## 508_Trim_R1.fastq.gz        4846     4195      4127      4087   3873
## 509_Trim_R1.fastq.gz       31810    27287     26782     26568  24933
## 510_Trim_R1.fastq.gz       17493    14980     14728     14579  13701
## 511_Trim_R1.fastq.gz       16696    14268     14037     13912  13125
## Fecal_kit_Trim_R1.fastq.gz  7136     6431      6213      6246   5847
## Plant_kit_Trim_R1.fastq.gz 10475     9326      9114      9144   8641
##                            nonchim
## 282_Trim_R1.fastq.gz          6771
## 283_Trim_R1.fastq.gz         10316
## 284_Trim_R1.fastq.gz          6997
## 285_Trim_R1.fastq.gz          7089
## 286_Trim_R1.fastq.gz          8842
## 287_Trim_R1.fastq.gz          7300
## 288_Trim_R1.fastq.gz          3946
## 289_Trim_R1.fastq.gz          4159
## 290_Trim_R1.fastq.gz          9108
## 291_Trim_R1.fastq.gz          3992
## 292_Trim_R1.fastq.gz          6894
## 293_Trim_R1.fastq.gz          6690
## 294_Trim_R1.fastq.gz          4234
## 295_Trim_R1.fastq.gz          5501
## 296_Trim_R1.fastq.gz          6513
## 297_Trim_R1.fastq.gz          5571
## 298_Trim_R1.fastq.gz          8348
## 299_Trim_R1.fastq.gz          6987
## 300_Trim_R1.fastq.gz          6354
## 301_Trim_R1.fastq.gz          5710
## 302_Trim_R1.fastq.gz          5085
## 303_Trim_R1.fastq.gz          5411
## 304_Trim_R1.fastq.gz          6777
## 306_Trim_R1.fastq.gz          6859
## 307_Trim_R1.fastq.gz          4205
## 308_Trim_R1.fastq.gz          7033
## 309_Trim_R1.fastq.gz          9302
## 310_Trim_R1.fastq.gz          7800
## 311_Trim_R1.fastq.gz         10718
## 312_Trim_R1.fastq.gz          6091
## 314_Trim_R1.fastq.gz          4646
## 359_Trim_R1.fastq.gz          8447
## 360_Trim_R1.fastq.gz          9124
## 361_Trim_R1.fastq.gz         10133
## 362_Trim_R1.fastq.gz          7114
## 363_Trim_R1.fastq.gz          5086
## 365_Trim_R1.fastq.gz          5373
## 366_Trim_R1.fastq.gz          5108
## 367_Trim_R1.fastq.gz          5396
## 368_Trim_R1.fastq.gz          6523
## 369_Trim_R1.fastq.gz         12909
## 370_Trim_R1.fastq.gz          9068
## 371_Trim_R1.fastq.gz          9325
## 372_Trim_R1.fastq.gz         12123
## 373_Trim_R1.fastq.gz         11506
## 374_Trim_R1.fastq.gz          9155
## 375_Trim_R1.fastq.gz          9677
## 376_Trim_R1.fastq.gz         10412
## 378_Trim_R1.fastq.gz         10388
## 379_Trim_R1.fastq.gz          9705
## 380_Trim_R1.fastq.gz          9308
## 381_Trim_R1.fastq.gz          9710
## 382_Trim_R1.fastq.gz         16323
## 383_Trim_R1.fastq.gz          6608
## 384_Trim_R1.fastq.gz          8923
## 385_Trim_R1.fastq.gz          7279
## 386_Trim_R1.fastq.gz         11864
## 387_Trim_R1.fastq.gz         14877
## 388_Trim_R1.fastq.gz         10229
## 389_Trim_R1.fastq.gz         10542
## 390_Trim_R1.fastq.gz          2189
## 505_Trim_R1.fastq.gz          4867
## 506_Trim_R1.fastq.gz          8152
## 507_Trim_R1.fastq.gz          5755
## 508_Trim_R1.fastq.gz          3833
## 509_Trim_R1.fastq.gz         24624
## 510_Trim_R1.fastq.gz         13462
## 511_Trim_R1.fastq.gz         12964
## Fecal_kit_Trim_R1.fastq.gz    5807
## Plant_kit_Trim_R1.fastq.gz    8562

This shows the library sizes of the samples and how many reads were removed at each step. There is 7.4796110^{5} cleaned reads that entered the DADA2 pipeline. We will now get read stats for the input ASVs.

## [1] 747961

We compare this to the read stats for the final libraries.

Making phyloseq object

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5607 taxa and 70 samples ]
## sample_data() Sample Data:       [ 70 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5607 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5607 tips and 5605 internal nodes ]

Cleaning data

Currently, we are starting with 5,607 ASVs from 70 samples

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5607 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5607 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5607 tips and 5605 internal nodes ]

First, we remove the kit samples to bring us down to 68 samples. We will look at these again later. We will also remove ASVs that aren’t present in any samples.

There was no empty samples or taxa which is what we want. Also, there was 16 ASVs that weren’t in any sample and were removed.

More cleaning of data

To start cleaning the data we will at the number of ASVs assigned to each phylum.

## 
##     Actinobacteria      Bacteroidetes        Chloroflexi 
##                 96               1257                 39 
##      Cyanobacteria    Deferribacteres      Elusimicrobia 
##                 74                  1                 16 
## Epsilonbacteraeota      Euryarchaeota      Fibrobacteres 
##                  2                 44                 39 
##         Firmicutes       Fusobacteria   Gemmatimonadetes 
##               3095                  4                  1 
## Kiritimatiellaeota      Lentisphaerae    Patescibacteria 
##                180                 31                 14 
##     Planctomycetes     Proteobacteria       Spirochaetes 
##                 15                222                138 
##      Synergistetes        Tenericutes    Verrucomicrobia 
##                  6                188                 35 
##               <NA> 
##                 94

Next we will count what samples have the ASVs that aren’t assigned to a phylum.

There are 94 ASVs that weren’t able to be assigned to a phylum. These unassigned taxa are found in all sample types with most of the unassigned ASVs in solid samples. NOTE that the sum column is reads not the number of ASVs! We next made a fasta file from the phyloseq object with these unknown taxa so that we can blast it later.

Getting back to our orginal phyloseq object: the 94 AVSs that weren’t assigned to a phyla were removed for analysis. This leaves 5,497 ASVs.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5497 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5497 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5497 tips and 5495 internal nodes ]

Next we will compute the total and average prevalences of the ASVs in each phylum. We are defining prevalence as the number of samples in which a taxon appears at least once.

Prevelance of Phyla
Phylum	1	2
Actinobacteria	19.78125	1899
Bacteroidetes	22.49483	28276
Chloroflexi	28.66667	1118
Cyanobacteria	14.45946	1070
Deferribacteres	1.00000	1
Elusimicrobia	23.43750	375
Epsilonbacteraeota	19.00000	38
Euryarchaeota	31.36364	1380
Fibrobacteres	31.00000	1209
Firmicutes	22.81874	70624
Fusobacteria	9.50000	38
Gemmatimonadetes	1.00000	1
Kiritimatiellaeota	19.97778	3596
Lentisphaerae	15.12903	469
Patescibacteria	26.00000	364
Planctomycetes	20.06667	301
Proteobacteria	15.32432	3402
Spirochaetes	21.03623	2903
Synergistetes	19.50000	117
Tenericutes	19.53191	3672
Verrucomicrobia	18.42857	645

Here we see that Deferribacteres and Gemmatimonadetes ASVs only has one feature so we’ll just looking into this real quick.

## [1] "Stomach Tube"

## OTU Table:          [1 taxa and 1 samples]
##                      taxa are rows
##          282
## ASV_5560   3

## [1] "Feces"

## OTU Table:          [1 taxa and 1 samples]
##                      taxa are rows
##          370
## ASV_5602   2

The phylum Deferribacteres are only in Fecal samples (2 reads) and and Gemmatimonadetes are only in Stomach Tube samples (3 reads). This suggest these groups might be important for comparing sample types, thus we will leave reads assigned to these phyla in the dataset despite their low prevelance.

Lastly, we’ll check to see if chloroplasts and Mitochondria are in the data set and remove them.

After removing chloroplasts and mitochondria there is 5,485 ASVs left.

Looking at metrics after filtering

As we have seen previously, there are 5485 ASVs in the dataset. This is composed of 21 phyla, 78 Orders, 116 Families and 293 Genera.

5393 ASVs didn’t have species assigned. Only 1.68% of taxa had species assigned. For genera, 1796 ASVs didn’t have a genera assigned. Only 67.3% of taxa had genera assigned.

Unassigned Species
Phylum	#ASVs with no species assignment	Total ASVs	Percent Unassigned
Actinobacteria	90	96	93.75000
Bacteroidetes	1244	1257	98.96579
Chloroflexi	39	39	100.00000
Cyanobacteria	65	65	100.00000
Deferribacteres	1	1	100.00000
Elusimicrobia	16	16	100.00000
Epsilonbacteraeota	2	2	100.00000
Euryarchaeota	44	44	100.00000
Fibrobacteres	34	39	87.17949
Firmicutes	3046	3095	98.41680
Fusobacteria	1	4	25.00000
Gemmatimonadetes	1	1	100.00000
Kiritimatiellaeota	180	180	100.00000
Lentisphaerae	31	31	100.00000
Patescibacteria	14	14	100.00000
Planctomycetes	15	15	100.00000
Proteobacteria	207	219	94.52055
Spirochaetes	135	138	97.82609
Synergistetes	6	6	100.00000
Tenericutes	188	188	100.00000
Verrucomicrobia	34	35	97.14286

This table gives the frequencing and percent of ASVs not assigned to species and their phyla. This really speaks to the limitations of the methods used here to be able to give species level assigments.

This table gives the frequencing and percent of ASVs not assigned to genus and their phyla.

There are 86 singletons (20), doubletons (37) or tripletons (29). This looks pretty good and indicates that filtering was not excessive nor was a large enough part of the data to be suspicious about. We will need these for diversity metrics.

For the last part of our cleaning process we will graph out the prevalance of ASVs assigned to each phylum.

Rechecking read stats

Before moving on we will look again at the read stats to check that we still don’t have reads that are too long in the dataset.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5485 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5485 taxa by 7 taxonomic ranks ]

## 
##  229  230  232  246  252  253  254  255  263  269  270  271  281  287  294 
##    3    7    1    1  851 4449  129    6    2    7   23    2    1    1    1 
##  342 
##    1

Looks like we now only have one sample that is greater than 300bp let’s see what it is.

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##                                                                                                                                                                                                                                                                                                                                                        Kingdom  
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Archaea"
##                                                                                                                                                                                                                                                                                                                                                        Phylum         
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Euryarchaeota"
##                                                                                                                                                                                                                                                                                                                                                        Class            
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteria"
##                                                                                                                                                                                                                                                                                                                                                        Order               
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteriales"
##                                                                                                                                                                                                                                                                                                                                                        Family               
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteriaceae"
##                                                                                                                                                                                                                                                                                                                                                        Genus               
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobrevibacter"
##                                                                                                                                                                                                                                                                                                                                                        Species
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG NA

As this large sequence is a Methanobrevibacter and this is a common rumen bacteria its expected to be here and will be left in the data set.

Abundance of Phyla

As the first part of the exploratory analysis we will look the general relative abundances of phyla across sample types.

Statistiscs for Abundance of Phyla
	Sample_Type	Phylum	mean	sd	sem
94	Solid	Firmicutes	67.171193	1.89788	0.547872
115	Stomach Tube	Firmicutes	64.680196	7.64829	2.207872
31	Grab Sample	Firmicutes	64.309812	6.22378	1.796650
10	Feces	Firmicutes	61.237127	3.58700	1.035479
73	Liquid Unstrained	Firmicutes	55.214891	6.56683	2.321726
52	Liquid Strained	Firmicutes	43.521396	3.83594	1.107340
44	Liquid Strained	Bacteroidetes	33.325984	3.48697	1.006602
2	Feces	Bacteroidetes	32.089477	3.22568	0.931172
65	Liquid Unstrained	Bacteroidetes	26.470699	2.42579	0.857646
107	Stomach Tube	Bacteroidetes	20.863182	4.86305	1.403841
86	Solid	Bacteroidetes	20.221741	2.76979	0.799571
23	Grab Sample	Bacteroidetes	19.959058	2.22827	0.643245
55	Liquid Strained	Kiritimatiellaeota	6.959357	1.43120	0.413151
39	Grab Sample	Spirochaetes	4.123484	7.67724	2.216229
76	Liquid Unstrained	Kiritimatiellaeota	3.954869	2.05528	0.726650
59	Liquid Strained	Proteobacteria	3.891003	1.39286	0.402083
113	Stomach Tube	Euryarchaeota	3.329381	1.35194	0.390270
92	Solid	Euryarchaeota	3.167559	1.78381	0.514941
80	Liquid Unstrained	Proteobacteria	3.012016	1.47040	0.519864
29	Grab Sample	Euryarchaeota	2.518253	0.87016	0.251193
71	Liquid Unstrained	Euryarchaeota	2.360323	1.42703	0.504532
60	Liquid Strained	Spirochaetes	2.259901	0.81533	0.235364
50	Liquid Strained	Euryarchaeota	2.202896	1.40978	0.406970
30	Grab Sample	Fibrobacteres	2.182511	0.52162	0.150579
62	Liquid Strained	Tenericutes	2.007239	0.41986	0.121202
81	Liquid Unstrained	Spirochaetes	1.937928	0.95423	0.337371
83	Liquid Unstrained	Tenericutes	1.883149	0.54376	0.192247
118	Stomach Tube	Kiritimatiellaeota	1.850052	1.30901	0.377879
122	Stomach Tube	Proteobacteria	1.813390	0.85311	0.246273
51	Liquid Strained	Fibrobacteres	1.790122	0.68267	0.197069
106	Stomach Tube	Actinobacteria	1.593072	0.44466	0.128362
38	Grab Sample	Proteobacteria	1.577367	0.39181	0.113107
125	Stomach Tube	Tenericutes	1.562888	0.47927	0.138353
101	Solid	Proteobacteria	1.514819	0.53489	0.154410
93	Solid	Fibrobacteres	1.440196	0.59696	0.172328
21	Feces	Verrucomicrobia	1.330008	0.53676	0.154950
41	Grab Sample	Tenericutes	1.327798	0.18652	0.053844
85	Solid	Actinobacteria	1.218782	0.30407	0.087779
102	Solid	Spirochaetes	1.117817	0.37786	0.109078
123	Stomach Tube	Spirochaetes	1.110958	0.63550	0.183454
22	Grab Sample	Actinobacteria	1.097541	0.22664	0.065427
104	Solid	Tenericutes	1.083357	0.17849	0.051527
17	Feces	Proteobacteria	1.076418	0.31832	0.091890
20	Feces	Tenericutes	0.974926	0.22835	0.065918
34	Grab Sample	Kiritimatiellaeota	0.949299	0.11497	0.033190
72	Liquid Unstrained	Fibrobacteres	0.924121	0.57314	0.202635
64	Liquid Unstrained	Actinobacteria	0.924064	0.33227	0.117476
46	Liquid Strained	Cyanobacteria	0.886615	0.36020	0.103981
13	Feces	Kiritimatiellaeota	0.842224	0.34891	0.100721
97	Solid	Kiritimatiellaeota	0.811684	0.13214	0.038147
99	Solid	Patescibacteria	0.696159	0.18816	0.054316
43	Liquid Strained	Actinobacteria	0.687316	0.30537	0.088154
87	Solid	Chloroflexi	0.680062	0.19086	0.055096
56	Liquid Strained	Lentisphaerae	0.671255	0.19280	0.055656
108	Stomach Tube	Chloroflexi	0.663903	0.15329	0.044252
8	Feces	Euryarchaeota	0.636827	0.34124	0.098507
67	Liquid Unstrained	Cyanobacteria	0.622941	0.41690	0.147396
77	Liquid Unstrained	Lentisphaerae	0.620633	0.41150	0.145487
126	Stomach Tube	Verrucomicrobia	0.609821	0.21143	0.061034
24	Grab Sample	Chloroflexi	0.584714	0.13518	0.039024
66	Liquid Unstrained	Chloroflexi	0.544889	0.08668	0.030645
84	Liquid Unstrained	Verrucomicrobia	0.540529	0.14486	0.051215
36	Grab Sample	Patescibacteria	0.531587	0.17283	0.049892
78	Liquid Unstrained	Patescibacteria	0.525094	0.16369	0.057872
57	Liquid Strained	Patescibacteria	0.480896	0.12887	0.037201
4	Feces	Cyanobacteria	0.449117	0.13271	0.038309
119	Stomach Tube	Lentisphaerae	0.442976	0.32682	0.094345
45	Liquid Strained	Chloroflexi	0.421857	0.11367	0.032813
1	Feces	Actinobacteria	0.407788	0.11409	0.032934
63	Liquid Strained	Verrucomicrobia	0.392914	0.11300	0.032619
120	Stomach Tube	Patescibacteria	0.365494	0.15142	0.043712
48	Liquid Strained	Elusimicrobia	0.363036	0.20188	0.058278
114	Stomach Tube	Fibrobacteres	0.354001	0.23941	0.069110
105	Solid	Verrucomicrobia	0.339158	0.06796	0.019618
42	Grab Sample	Verrucomicrobia	0.330473	0.10189	0.029413
18	Feces	Spirochaetes	0.328016	0.21602	0.062360
69	Liquid Unstrained	Elusimicrobia	0.317035	0.18254	0.064539
109	Stomach Tube	Cyanobacteria	0.274073	0.25401	0.073326
14	Feces	Lentisphaerae	0.237553	0.18456	0.053277
16	Feces	Planctomycetes	0.195166	0.07189	0.020753
111	Stomach Tube	Elusimicrobia	0.156546	0.13165	0.038005
90	Solid	Elusimicrobia	0.151592	0.08210	0.023700
25	Grab Sample	Cyanobacteria	0.139923	0.06311	0.018219
116	Stomach Tube	Fusobacteria	0.130143	0.11210	0.032361
121	Stomach Tube	Planctomycetes	0.126690	0.04305	0.012427
103	Solid	Synergistetes	0.121142	0.03615	0.010437
27	Grab Sample	Elusimicrobia	0.111197	0.04869	0.014056
100	Solid	Planctomycetes	0.102944	0.01891	0.005458
6	Feces	Elusimicrobia	0.097389	0.05545	0.016006
37	Grab Sample	Planctomycetes	0.096631	0.04228	0.012205
88	Solid	Cyanobacteria	0.095623	0.06059	0.017491
79	Liquid Unstrained	Planctomycetes	0.087836	0.03479	0.012301
35	Grab Sample	Lentisphaerae	0.077359	0.04240	0.012241
40	Grab Sample	Synergistetes	0.076985	0.04797	0.013848
58	Liquid Strained	Planctomycetes	0.064471	0.03202	0.009243
98	Solid	Lentisphaerae	0.056500	0.02380	0.006872
124	Stomach Tube	Synergistetes	0.052609	0.04184	0.012079
82	Liquid Unstrained	Synergistetes	0.048419	0.01954	0.006910
61	Liquid Strained	Synergistetes	0.045930	0.02969	0.008572
7	Feces	Epsilonbacteraeota	0.036546	0.02753	0.007948
3	Feces	Chloroflexi	0.033252	0.01365	0.003940
49	Liquid Strained	Epsilonbacteraeota	0.020465	0.02449	0.007068
9	Feces	Fibrobacteres	0.017672	0.01711	0.004938
112	Stomach Tube	Epsilonbacteraeota	0.016921	0.02402	0.006934
53	Liquid Strained	Fusobacteria	0.007350	0.01514	0.004369
91	Solid	Epsilonbacteraeota	0.006537	0.00899	0.002595
70	Liquid Unstrained	Epsilonbacteraeota	0.005759	0.00860	0.003042
15	Feces	Patescibacteria	0.005358	0.00988	0.002851
74	Liquid Unstrained	Fusobacteria	0.004807	0.01090	0.003854
117	Stomach Tube	Gemmatimonadetes	0.003704	0.01283	0.003704
95	Solid	Fusobacteria	0.003135	0.00469	0.001353
32	Grab Sample	Fusobacteria	0.003029	0.00707	0.002042
28	Grab Sample	Epsilonbacteraeota	0.002979	0.00739	0.002133
11	Feces	Fusobacteria	0.002610	0.00473	0.001365
5	Feces	Deferribacteres	0.001839	0.00637	0.001839
19	Feces	Synergistetes	0.000688	0.00238	0.000688
12	Feces	Gemmatimonadetes	0.000000	0.00000	0.000000
26	Grab Sample	Deferribacteres	0.000000	0.00000	0.000000
33	Grab Sample	Gemmatimonadetes	0.000000	0.00000	0.000000
47	Liquid Strained	Deferribacteres	0.000000	0.00000	0.000000
54	Liquid Strained	Gemmatimonadetes	0.000000	0.00000	0.000000
68	Liquid Unstrained	Deferribacteres	0.000000	0.00000	0.000000
75	Liquid Unstrained	Gemmatimonadetes	0.000000	0.00000	0.000000
89	Solid	Deferribacteres	0.000000	0.00000	0.000000
96	Solid	Gemmatimonadetes	0.000000	0.00000	0.000000
110	Stomach Tube	Deferribacteres	0.000000	0.00000	0.000000

We will look at relative abundance of Phyla in certain sample types. First, grab samples.

Next, we examine the relative abundance of Phyla in only fecal samples.

These are the phyla found in all samples sorted by decending order of mean relative abundance.

We will have a look to see if any phyla only present in only feces or only in stomach tube samples.

Deferribacteres Was only found in fecal samples and Gemmatimonadetes was only found in stomach tube samples.

This confirms what we say earlier and we didn’t identify any other phyla that are only present in these sample types.

Next we will graph out some of the different phyla based on their abundance ranges.

This is a graph of the major phyla, defined as those present at an abundance greater than 3% relative abundance, in rumen samples. Next we will graph phyla less than 3% relative abundance.

This is a graph of the “minor” phyla, defined as present at an abundance below 3%, in rumen samples. I also made an interactive version of this graph to put a link for in the manuscript.

You can access the interactive figure here.Below is Figure 1 A & B.

## Saving 180 x 152 mm image

We will do the create the same graphs at the family level as well.

Abundance of families

This is a table of the relative abundances of families in all sample types.

Statistiscs for Abundance of fam
	Sample_Type	Family	mean	sd	sem
96	Feces	Ruminococcaceae	40.662043	2.17531	0.627959
171	Grab Sample	Lachnospiraceae	25.909379	2.13026	0.614953
516	Solid	Lachnospiraceae	24.978741	2.41347	0.696708
631	Stomach Tube	Lachnospiraceae	23.893818	3.88265	1.120824
320	Liquid Strained	Prevotellaceae	23.776220	3.98548	1.150509
556	Solid	Ruminococcaceae	19.590277	0.60315	0.174115
487	Solid	Christensenellaceae	19.580047	1.68893	0.487552
602	Stomach Tube	Christensenellaceae	18.574572	1.73189	0.499955
441	Liquid Unstrained	Ruminococcaceae	18.461506	1.59136	0.562629
142	Grab Sample	Christensenellaceae	18.085232	2.72055	0.785356
671	Stomach Tube	Ruminococcaceae	17.918312	1.45935	0.421278
401	Liquid Unstrained	Lachnospiraceae	17.835313	2.41513	0.853876
211	Grab Sample	Ruminococcaceae	17.481760	2.51743	0.726720
372	Liquid Unstrained	Christensenellaceae	16.812558	2.68812	0.950394
435	Liquid Unstrained	Prevotellaceae	16.146729	2.34486	0.829034
95	Feces	Rikenellaceae	15.692367	2.04158	0.589352
326	Liquid Strained	Ruminococcaceae	15.458665	1.76966	0.510857
286	Liquid Strained	Lachnospiraceae	15.089913	1.75205	0.505772
257	Liquid Strained	Christensenellaceae	12.142322	1.44194	0.416253
665	Stomach Tube	Prevotellaceae	10.533860	3.46172	0.999311
550	Solid	Prevotellaceae	9.172494	1.41162	0.407499
205	Grab Sample	Prevotellaceae	8.656660	1.49577	0.431791
555	Solid	Rikenellaceae	7.756655	1.17414	0.338944
56	Feces	Lachnospiraceae	7.718256	1.85419	0.535258
27	Feces	Christensenellaceae	7.483265	1.06576	0.307660
210	Grab Sample	Rikenellaceae	7.475779	1.14093	0.329358
11	Feces	Bacteroidaceae	7.403751	0.87114	0.251478
670	Stomach Tube	Rikenellaceae	7.375575	1.78391	0.514971
440	Liquid Unstrained	Rikenellaceae	6.348289	1.01506	0.358878
90	Feces	Prevotellaceae	6.258670	1.21983	0.352134
325	Liquid Strained	Rikenellaceae	5.326237	1.30835	0.377688
217	Grab Sample	Spirochaetaceae	4.279276	8.11607	2.342907
277	Liquid Strained	F082	4.166934	0.94223	0.271998
638	Stomach Tube	Methanobacteriaceae	3.290438	1.39475	0.402629
523	Solid	Methanobacteriaceae	3.006646	1.84641	0.533014
86	Feces	Peptostreptococcaceae	2.894522	0.89910	0.259548
392	Liquid Unstrained	F082	2.882237	0.41067	0.145192
624	Stomach Tube	Family_XIII	2.719298	0.57073	0.164756
509	Solid	Family_XIII	2.651126	0.58246	0.168141
49	Feces	Family_XIII	2.577243	0.65975	0.190455
178	Grab Sample	Methanobacteriaceae	2.464815	0.92852	0.268041
164	Grab Sample	Family_XIII	2.446497	0.58196	0.167996
332	Liquid Strained	Spirochaetaceae	2.408240	0.91161	0.263159
408	Liquid Unstrained	Methanobacteriaceae	2.287936	1.46200	0.516895
165	Grab Sample	Fibrobacteraceae	2.286694	0.54644	0.157744
293	Liquid Strained	Methanobacteriaceae	2.243293	1.52734	0.440906
342	Liquid Strained	Veillonellaceae	2.113366	0.56986	0.164503
394	Liquid Unstrained	Family_XIII	2.030927	0.50719	0.179319
447	Liquid Unstrained	Spirochaetaceae	2.023389	1.06782	0.377533
280	Liquid Strained	Fibrobacteraceae	2.017938	0.79045	0.228183
622	Stomach Tube	F082	1.883605	0.94966	0.274142
250	Liquid Strained	Burkholderiaceae	1.613253	1.14707	0.331132
162	Grab Sample	F082	1.573685	0.31899	0.092086
457	Liquid Unstrained	Veillonellaceae	1.558952	0.80191	0.283518
336	Liquid Strained	Succinivibrionaceae	1.543685	0.60789	0.175483
620	Stomach Tube	Erysipelotrichaceae	1.537342	0.29198	0.084288
510	Solid	Fibrobacteraceae	1.505930	0.62518	0.180473
507	Solid	F082	1.479020	0.40472	0.116833
5	Feces	Akkermansiaceae	1.399232	0.56693	0.163658
243	Liquid Strained	Bacteroidales_RF16_group	1.369223	0.39137	0.112979
308	Liquid Strained	p-251-o5	1.337976	0.62608	0.180735
279	Liquid Strained	Family_XIII	1.318429	0.37085	0.107056
365	Liquid Unstrained	Burkholderiaceae	1.116637	0.97066	0.343179
562	Solid	Spirochaetaceae	1.100219	0.34829	0.100541
677	Stomach Tube	Spirochaetaceae	1.099645	0.62883	0.181527
680	Stomach Tube	Streptococcaceae	1.095366	0.92407	0.266756
275	Liquid Strained	Erysipelotrichaceae	1.070523	0.37997	0.109687
390	Liquid Unstrained	Erysipelotrichaceae	1.065354	0.19851	0.070183
451	Liquid Unstrained	Succinivibrionaceae	1.052210	0.67959	0.240271
237	Liquid Strained	Anaeroplasmataceae	1.026677	0.33767	0.097476
395	Liquid Unstrained	Fibrobacteraceae	1.017878	0.65786	0.232590
583	Stomach Tube	Atopobiaceae	1.006651	0.40293	0.116316
463	Solid	Acidaminococcaceae	0.980055	0.25973	0.074976
160	Grab Sample	Erysipelotrichaceae	0.972573	0.17214	0.049692
352	Liquid Unstrained	Anaeroplasmataceae	0.951233	0.35690	0.126184
358	Liquid Unstrained	Bacteroidales_RF16_group	0.869041	0.28465	0.100640
423	Liquid Unstrained	p-251-o5	0.851984	0.25395	0.089786
505	Solid	Erysipelotrichaceae	0.840776	0.18666	0.053883
45	Feces	Erysipelotrichaceae	0.825341	0.17601	0.050811
227	Grab Sample	Veillonellaceae	0.748046	0.18592	0.053671
79	Feces	p-2534-18B5_gut_group	0.745844	0.49756	0.143633
466	Solid	Anaerolineaceae	0.710695	0.19884	0.057401
581	Stomach Tube	Anaerolineaceae	0.699699	0.15876	0.045830
13	Feces	Bacteroidales_RF16_group	0.681372	0.16245	0.046895
348	Liquid Unstrained	Acidaminococcaceae	0.679111	0.18720	0.066184
687	Stomach Tube	Veillonellaceae	0.677002	0.41223	0.119001
341	Liquid Strained	vadinBE97	0.668188	0.20766	0.059946
357	Liquid Unstrained	Bacteroidales_BS11_gut_group	0.647920	0.23197	0.082014
353	Liquid Unstrained	Atopobiaceae	0.644468	0.30347	0.107292
242	Liquid Strained	Bacteroidales_BS11_gut_group	0.636461	0.16085	0.046432
127	Grab Sample	Bacteroidales_BS11_gut_group	0.633199	0.16352	0.047204
472	Solid	Bacteroidales_BS11_gut_group	0.626981	0.16838	0.048607
456	Liquid Unstrained	vadinBE97	0.619314	0.42255	0.149393
121	Grab Sample	Anaerolineaceae	0.612631	0.14162	0.040881
63	Feces	Methanobacteriaceae	0.596446	0.37468	0.108160
351	Liquid Unstrained	Anaerolineaceae	0.590020	0.08645	0.030563
118	Grab Sample	Acidaminococcaceae	0.577466	0.10489	0.030280
500	Solid	Eggerthellaceae	0.566750	0.12475	0.036012
36	Feces	Desulfovibrionaceae	0.560810	0.27123	0.078297
496	Solid	Desulfovibrionaceae	0.559735	0.21469	0.061977
123	Grab Sample	Atopobiaceae	0.556082	0.11200	0.032332
582	Stomach Tube	Anaeroplasmataceae	0.550660	0.27169	0.078429
193	Grab Sample	p-251-o5	0.534799	0.26332	0.076013
468	Solid	Atopobiaceae	0.533660	0.15493	0.044724
151	Grab Sample	Desulfovibrionaceae	0.530917	0.17663	0.050988
238	Liquid Strained	Atopobiaceae	0.524360	0.29423	0.084937
611	Stomach Tube	Desulfovibrionaceae	0.523125	0.17801	0.051387
578	Stomach Tube	Acidaminococcaceae	0.520036	0.17769	0.051296
85	Feces	Peptococcaceae	0.510863	0.10803	0.031186
530	Solid	Muribaculaceae	0.501963	0.06935	0.020019
233	Liquid Strained	Acidaminococcaceae	0.482755	0.14870	0.042927
615	Stomach Tube	Eggerthellaceae	0.478785	0.15600	0.045032
155	Grab Sample	Eggerthellaceae	0.475405	0.13575	0.039188
236	Liquid Strained	Anaerolineaceae	0.473437	0.12683	0.036612
185	Grab Sample	Muribaculaceae	0.463656	0.09160	0.026444
587	Stomach Tube	Bacteroidales_BS11_gut_group	0.447419	0.23030	0.066483
686	Stomach Tube	vadinBE97	0.435754	0.34089	0.098407
588	Stomach Tube	Bacteroidales_RF16_group	0.420013	0.26444	0.076336
381	Liquid Unstrained	Desulfovibrionaceae	0.392658	0.11058	0.039095
221	Grab Sample	Succinivibrionaceae	0.380597	0.18977	0.054781
625	Stomach Tube	Fibrobacteraceae	0.377099	0.25939	0.074878
645	Stomach Tube	Muribaculaceae	0.369579	0.17473	0.050440
572	Solid	Veillonellaceae	0.368549	0.10245	0.029575
259	Liquid Strained	Clostridiales_vadinBB60_group	0.356928	0.09081	0.026215
102	Feces	Spirochaetaceae	0.347187	0.22783	0.065768
47	Feces	F082	0.341935	0.12590	0.036343
681	Stomach Tube	Succinivibrionaceae	0.336053	0.27571	0.079590
595	Stomach Tube	Burkholderiaceae	0.331625	0.27181	0.078465
3	Feces	Acidaminococcaceae	0.319192	0.06945	0.020049
122	Grab Sample	Anaeroplasmataceae	0.307062	0.11445	0.033038
80	Feces	Paludibacteraceae	0.303656	0.13622	0.039325
266	Liquid Strained	Desulfovibrionaceae	0.299891	0.08871	0.025609
525	Solid	Methanomethylophilaceae	0.296907	0.08416	0.024296
653	Stomach Tube	p-251-o5	0.296192	0.18872	0.054478
70	Feces	Muribaculaceae	0.291696	0.10340	0.029848
538	Solid	p-251-o5	0.288969	0.09724	0.028071
415	Liquid Unstrained	Muribaculaceae	0.280209	0.11363	0.040174
374	Liquid Unstrained	Clostridiales_vadinBB60_group	0.258308	0.14999	0.053031
385	Liquid Unstrained	Eggerthellaceae	0.249293	0.09906	0.035025
271	Liquid Strained	Elusimicrobiaceae	0.247167	0.10371	0.029938
29	Feces	Clostridiales_vadinBB60_group	0.245353	0.15311	0.044200
410	Liquid Unstrained	Methanomethylophilaceae	0.243601	0.08607	0.030432
480	Solid	Burkholderiaceae	0.239162	0.24901	0.071882
128	Grab Sample	Bacteroidales_RF16_group	0.228827	0.07427	0.021439
566	Solid	Succinivibrionaceae	0.225922	0.16580	0.047861
335	Liquid Strained	Streptococcaceae	0.215900	0.10879	0.031406
135	Grab Sample	Burkholderiaceae	0.209240	0.10020	0.028926
295	Liquid Strained	Methanomethylophilaceae	0.208475	0.09661	0.027889
87	Feces	Pirellulaceae	0.206561	0.07625	0.022010
640	Stomach Tube	Methanomethylophilaceae	0.202565	0.07348	0.021210
113	Feces	Victivallaceae	0.198879	0.15588	0.044999
149	Grab Sample	Defluviitaleaceae	0.196038	0.08053	0.023248
40	Feces	Eggerthellaceae	0.189249	0.08373	0.024170
300	Liquid Strained	Muribaculaceae	0.181475	0.09106	0.026286
450	Liquid Unstrained	Streptococcaceae	0.179921	0.08149	0.028811
270	Liquid Strained	Eggerthellaceae	0.176277	0.08897	0.025683
200	Grab Sample	Peptococcaceae	0.175800	0.10497	0.030303
386	Liquid Unstrained	Elusimicrobiaceae	0.175441	0.11458	0.040510
387	Liquid Unstrained	Endomicrobiaceae	0.173038	0.12007	0.042452
180	Grab Sample	Methanomethylophilaceae	0.170696	0.06650	0.019196
545	Solid	Peptococcaceae	0.167197	0.05052	0.014583
609	Stomach Tube	Defluviitaleaceae	0.166117	0.06242	0.018019
467	Solid	Anaeroplasmataceae	0.162214	0.05784	0.016697
473	Solid	Bacteroidales_RF16_group	0.161196	0.07571	0.021855
272	Liquid Strained	Endomicrobiaceae	0.159378	0.14788	0.042690
494	Solid	Defluviitaleaceae	0.148982	0.04836	0.013962
604	Stomach Tube	Clostridiales_vadinBB60_group	0.143844	0.12588	0.036339
660	Stomach Tube	Peptococcaceae	0.143545	0.07142	0.020618
28	Feces	Clostridiaceae_1	0.137297	0.06146	0.017742
617	Stomach Tube	Endomicrobiaceae	0.134121	0.12862	0.037130
662	Stomach Tube	Pirellulaceae	0.133296	0.04368	0.012609
502	Solid	Endomicrobiaceae	0.132840	0.07372	0.021281
565	Solid	Streptococcaceae	0.130788	0.16399	0.047341
19	Feces	Bifidobacteriaceae	0.128085	0.06899	0.019915
567	Solid	Synergistaceae	0.126694	0.03795	0.010956
177	Grab Sample	Marinilabiliaceae	0.122366	0.04732	0.013661
220	Grab Sample	Streptococcaceae	0.113880	0.08490	0.024509
379	Liquid Unstrained	Defluviitaleaceae	0.113587	0.04419	0.015625
475	Solid	Bacteroidetes_BD2-2	0.110198	0.05620	0.016224
547	Solid	Pirellulaceae	0.107592	0.01948	0.005622
130	Grab Sample	Bacteroidetes_BD2-2	0.106388	0.04375	0.012630
627	Stomach Tube	Fusobacteriaceae	0.105689	0.09255	0.026717
41	Feces	Elusimicrobiaceae	0.102092	0.05904	0.017042
202	Grab Sample	Pirellulaceae	0.101176	0.04403	0.012711
522	Solid	Marinilabiliaceae	0.097609	0.06302	0.018191
8	Feces	Atopobiaceae	0.095450	0.04035	0.011648
432	Liquid Unstrained	Pirellulaceae	0.094921	0.03686	0.013033
20	Feces	Burkholderiaceae	0.089456	0.04516	0.013035
430	Liquid Unstrained	Peptococcaceae	0.088746	0.07321	0.025885
157	Grab Sample	Endomicrobiaceae	0.088366	0.05187	0.014973
343	Liquid Strained	Victivallaceae	0.086966	0.04126	0.011909
222	Grab Sample	Synergistaceae	0.080729	0.05044	0.014561
407	Liquid Unstrained	Marinilabiliaceae	0.079882	0.04409	0.015587
428	Liquid Unstrained	Pedosphaeraceae	0.078697	0.03959	0.013997
637	Stomach Tube	Marinilabiliaceae	0.078628	0.07002	0.020213
16	Feces	Barnesiellaceae	0.076851	0.02568	0.007414
544	Solid	PeH15	0.074235	0.02913	0.008409
313	Liquid Strained	Pedosphaeraceae	0.073596	0.06269	0.018096
34	Feces	Defluviitaleaceae	0.073182	0.03254	0.009394
64	Feces	Methanocorpusculaceae	0.072398	0.05968	0.017228
317	Liquid Strained	Pirellulaceae	0.072235	0.03548	0.010242
606	Stomach Tube	Coriobacteriales_Incertae_Sedis	0.071326	0.05090	0.014695
586	Stomach Tube	Bacteroidaceae	0.071087	0.11475	0.033127
226	Grab Sample	vadinBE97	0.070891	0.04038	0.011656
287	Liquid Strained	Lactobacillaceae	0.069775	0.06637	0.019159
161	Grab Sample	Eubacteriaceae	0.068736	0.03572	0.010310
658	Stomach Tube	Pedosphaeraceae	0.067406	0.06005	0.017336
61	Feces	Marinifilaceae	0.066216	0.04162	0.012014
659	Stomach Tube	PeH15	0.064715	0.03626	0.010466
458	Liquid Unstrained	Victivallaceae	0.064524	0.05513	0.019492
199	Grab Sample	PeH15	0.063409	0.04192	0.012101
621	Stomach Tube	Eubacteriaceae	0.063345	0.03978	0.011483
78	Feces	p-251-o5	0.062782	0.05180	0.014954
264	Liquid Strained	Defluviitaleaceae	0.062671	0.03757	0.010845
657	Stomach Tube	Pasteurellaceae	0.061972	0.06716	0.019389
311	Liquid Strained	Paracaedibacteraceae	0.061309	0.03007	0.008679
53	Feces	GZKB124	0.060164	0.11122	0.032107
623	Stomach Tube	Family_XI	0.059822	0.06603	0.019060
321	Liquid Strained	Pseudomonadaceae	0.059767	0.06805	0.019645
529	Solid	Moraxellaceae	0.059274	0.16647	0.048055
506	Solid	Eubacteriaceae	0.059031	0.03127	0.009028
88	Feces	Planococcaceae	0.058235	0.07061	0.020384
402	Liquid Unstrained	Lactobacillaceae	0.058117	0.03608	0.012757
146	Grab Sample	Coriobacteriales_Incertae_Sedis	0.057232	0.02890	0.008343
491	Solid	Coriobacteriales_Incertae_Sedis	0.056256	0.02149	0.006204
292	Liquid Strained	Marinilabiliaceae	0.056163	0.04938	0.014256
682	Stomach Tube	Synergistaceae	0.056113	0.04641	0.013396
632	Stomach Tube	Lactobacillaceae	0.055846	0.04092	0.011811
315	Liquid Strained	Peptococcaceae	0.055806	0.03613	0.010430
543	Solid	Pedosphaeraceae	0.055375	0.03722	0.010745
571	Solid	vadinBE97	0.053217	0.02680	0.007737
452	Liquid Unstrained	Synergistaceae	0.052819	0.02235	0.007901
492	Solid	Corynebacteriaceae	0.052490	0.10735	0.030990
111	Feces	vadinBE97	0.052321	0.04605	0.013293
337	Liquid Strained	Synergistaceae	0.051608	0.03343	0.009650
426	Liquid Unstrained	Paracaedibacteraceae	0.051468	0.03729	0.013182
109	Feces	Tannerellaceae	0.051042	0.03069	0.008859
391	Liquid Unstrained	Eubacteriaceae	0.050990	0.03438	0.012154
356	Liquid Unstrained	Bacteroidaceae	0.049972	0.03979	0.014067
14	Feces	Bacteroidales_UCG-001	0.048206	0.02883	0.008322
258	Liquid Strained	Clostridiaceae_1	0.047419	0.03865	0.011159
429	Liquid Unstrained	PeH15	0.046158	0.02941	0.010398
416	Liquid Unstrained	Mycoplasmataceae	0.045288	0.03608	0.012755
436	Liquid Unstrained	Pseudomonadaceae	0.045214	0.03532	0.012487
474	Solid	Bacteroidales_UCG-001	0.044178	0.02459	0.007097
661	Stomach Tube	Peptostreptococcaceae	0.043530	0.01594	0.004601
152	Grab Sample	Desulfuromonadaceae	0.042774	0.02832	0.008176
597	Stomach Tube	Cardiobacteriaceae	0.042566	0.03387	0.009777
198	Grab Sample	Pedosphaeraceae	0.042548	0.03695	0.010668
541	Solid	Paracaedibacteraceae	0.040868	0.03335	0.009629
656	Stomach Tube	Paracaedibacteraceae	0.040550	0.02568	0.007413
590	Stomach Tube	Bacteroidetes_BD2-2	0.039367	0.02317	0.006689
105	Feces	Streptococcaceae	0.039274	0.02798	0.008078
2	Feces	Acetobacteraceae	0.039145	0.03724	0.010751
21	Feces	Campylobacteraceae	0.038741	0.02917	0.008419
497	Solid	Desulfuromonadaceae	0.038547	0.02360	0.006813
688	Stomach Tube	Victivallaceae	0.038405	0.03573	0.010315
241	Liquid Strained	Bacteroidaceae	0.037620	0.03860	0.011143
323	Liquid Strained	Rhizobiaceae	0.037541	0.03476	0.010035
231	Liquid Strained	0319-6G20	0.037199	0.02142	0.006184
644	Stomach Tube	Moraxellaceae	0.037051	0.04045	0.011677
129	Grab Sample	Bacteroidales_UCG-001	0.036976	0.02393	0.006907
316	Liquid Strained	Peptostreptococcaceae	0.036531	0.03227	0.009316
553	Solid	Rhizobiaceae	0.035823	0.03217	0.009286
360	Liquid Unstrained	Bacteroidetes_BD2-2	0.035561	0.01890	0.006682
126	Grab Sample	Bacteroidaceae	0.035532	0.02987	0.008624
6	Feces	Anaerolineaceae	0.035167	0.01434	0.004140
589	Stomach Tube	Bacteroidales_UCG-001	0.034726	0.03563	0.010285
346	Liquid Unstrained	0319-6G20	0.034156	0.03848	0.013604
382	Liquid Unstrained	Desulfuromonadaceae	0.033825	0.01931	0.006827
616	Stomach Tube	Elusimicrobiaceae	0.033798	0.02366	0.006829
642	Stomach Tube	Microbacteriaceae	0.032809	0.03284	0.009479
546	Solid	Peptostreptococcaceae	0.032794	0.02061	0.005950
431	Liquid Unstrained	Peptostreptococcaceae	0.032204	0.01756	0.006207
57	Feces	Lactobacillaceae	0.031440	0.02677	0.007727
359	Liquid Unstrained	Bacteroidales_UCG-001	0.031398	0.02176	0.007693
668	Stomach Tube	Rhizobiaceae	0.030916	0.03065	0.008848
517	Solid	Lactobacillaceae	0.030634	0.02465	0.007115
633	Stomach Tube	Leptotrichiaceae	0.030396	0.05006	0.014450
245	Liquid Strained	Bacteroidetes_BD2-2	0.030274	0.01563	0.004511
377	Liquid Unstrained	Corynebacteriaceae	0.029443	0.03101	0.010962
446	Liquid Unstrained	Sphingomonadaceae	0.029357	0.03590	0.012692
607	Stomach Tube	Corynebacteriaceae	0.029047	0.02805	0.008098
143	Grab Sample	Clostridiaceae_1	0.027773	0.02463	0.007111
471	Solid	Bacteroidaceae	0.027522	0.02366	0.006831
201	Grab Sample	Peptostreptococcaceae	0.027319	0.01781	0.005141
666	Stomach Tube	Pseudomonadaceae	0.026882	0.03445	0.009944
244	Liquid Strained	Bacteroidales_UCG-001	0.026616	0.02990	0.008630
156	Grab Sample	Elusimicrobiaceae	0.026613	0.02532	0.007308
647	Stomach Tube	Neisseriaceae	0.026201	0.03804	0.010980
176	Grab Sample	Marinifilaceae	0.025995	0.02105	0.006077
172	Grab Sample	Lactobacillaceae	0.025950	0.02155	0.006222
676	Stomach Tube	Sphingomonadaceae	0.025676	0.02909	0.008398
388	Liquid Unstrained	Enterobacteriaceae	0.025077	0.01960	0.006928
501	Solid	Elusimicrobiaceae	0.024949	0.01781	0.005143
144	Grab Sample	Clostridiales_vadinBB60_group	0.024787	0.02238	0.006461
373	Liquid Unstrained	Clostridiaceae_1	0.024771	0.00887	0.003136
110	Feces	Terasakiellaceae	0.024248	0.02840	0.008198
561	Solid	Sphingomonadaceae	0.024161	0.02685	0.007751
331	Liquid Strained	Sphingomonadaceae	0.024039	0.03042	0.008781
618	Stomach Tube	Enterobacteriaceae	0.024030	0.02673	0.007718
437	Liquid Unstrained	Puniceicoccaceae	0.023500	0.02735	0.009669
376	Liquid Unstrained	Coriobacteriales_Incertae_Sedis	0.023124	0.01752	0.006196
520	Solid	M2PB4-65_termite_group	0.022957	0.01940	0.005599
251	Liquid Strained	Campylobacteraceae	0.022911	0.02738	0.007905
186	Grab Sample	Mycoplasmataceae	0.022419	0.02510	0.007247
46	Feces	Eubacteriaceae	0.022333	0.01495	0.004316
498	Solid	Devosiaceae	0.022316	0.01422	0.004105
612	Stomach Tube	Desulfuromonadaceae	0.022204	0.02251	0.006498
208	Grab Sample	Rhizobiaceae	0.022144	0.02111	0.006094
314	Liquid Strained	PeH15	0.022031	0.02670	0.007707
649	Stomach Tube	Nocardiaceae	0.021847	0.01359	0.003923
488	Solid	Clostridiaceae_1	0.021417	0.02079	0.006002
297	Liquid Strained	Microbacteriaceae	0.021216	0.02142	0.006184
301	Liquid Strained	Mycoplasmataceae	0.020624	0.02690	0.007766
196	Grab Sample	Paracaedibacteraceae	0.020053	0.01779	0.005135
380	Liquid Unstrained	Desulfobulbaceae	0.020019	0.02383	0.008426
655	Stomach Tube	Paludibacteraceae	0.020009	0.01491	0.004304
490	Solid	COB_P4-1_termite_group	0.019979	0.01485	0.004287
651	Stomach Tube	Oligoflexaceae	0.019945	0.02065	0.005960
153	Grab Sample	Devosiaceae	0.019573	0.01757	0.005071
262	Liquid Strained	Corynebacteriaceae	0.019564	0.02327	0.006717
265	Liquid Strained	Desulfobulbaceae	0.019531	0.01404	0.004054
521	Solid	Marinifilaceae	0.019393	0.01509	0.004357
322	Liquid Strained	Puniceicoccaceae	0.019346	0.02347	0.006774
527	Solid	Microbacteriaceae	0.019278	0.01399	0.004039
414	Liquid Unstrained	Moraxellaceae	0.019234	0.02319	0.008201
508	Solid	Family_XI	0.019088	0.03173	0.009160
664	Stomach Tube	Porphyromonadaceae	0.018788	0.02410	0.006958
50	Feces	Fibrobacteraceae	0.018699	0.01805	0.005210
603	Stomach Tube	Clostridiaceae_1	0.018597	0.01059	0.003057
596	Stomach Tube	Campylobacteraceae	0.018162	0.02628	0.007585
216	Grab Sample	Sphingomonadaceae	0.017641	0.01910	0.005513
584	Stomach Tube	Bacillaceae	0.016902	0.02553	0.007370
406	Liquid Unstrained	Marinifilaceae	0.016459	0.01805	0.006380
145	Grab Sample	COB_P4-1_termite_group	0.016232	0.02194	0.006333
289	Liquid Strained	Leuconostocaceae	0.016175	0.02517	0.007266
425	Liquid Unstrained	Paludibacteraceae	0.016139	0.01815	0.006415
646	Stomach Tube	Mycoplasmataceae	0.016099	0.01811	0.005228
568	Solid	Syntrophomonadaceae	0.015737	0.00967	0.002791
610	Stomach Tube	Desulfobulbaceae	0.015682	0.01561	0.004505
531	Solid	Mycoplasmataceae	0.015630	0.02135	0.006162
158	Grab Sample	Enterobacteriaceae	0.015240	0.02024	0.005844
663	Stomach Tube	Planococcaceae	0.015003	0.01817	0.005244
147	Grab Sample	Corynebacteriaceae	0.014852	0.01934	0.005584
672	Stomach Tube	Saccharimonadaceae	0.014464	0.01235	0.003564
350	Liquid Unstrained	Akkermansiaceae	0.014429	0.01506	0.005323
675	Stomach Tube	Sphingobacteriaceae	0.014413	0.01673	0.004829
330	Liquid Strained	Sphingobacteriaceae	0.014247	0.01833	0.005290
182	Grab Sample	Microbacteriaceae	0.014190	0.01921	0.005545
613	Stomach Tube	Devosiaceae	0.014048	0.01362	0.003931
540	Solid	Paludibacteraceae	0.013924	0.01456	0.004203
412	Liquid Unstrained	Microbacteriaceae	0.013779	0.01436	0.005077
445	Liquid Unstrained	Sphingobacteriaceae	0.013391	0.02110	0.007460
273	Liquid Strained	Enterobacteriaceae	0.013357	0.01312	0.003789
7	Feces	Anaeroplasmataceae	0.013311	0.01168	0.003371
299	Liquid Strained	Moraxellaceae	0.013064	0.01234	0.003563
175	Grab Sample	M2PB4-65_termite_group	0.013056	0.01620	0.004676
163	Grab Sample	Family_XI	0.012993	0.02246	0.006483
345	Liquid Strained	Xanthomonadaceae	0.012979	0.01750	0.005051
278	Liquid Strained	Family_XI	0.012832	0.01923	0.005552
291	Liquid Strained	Marinifilaceae	0.012604	0.01120	0.003233
393	Liquid Unstrained	Family_XI	0.012370	0.02313	0.008177
267	Liquid Strained	Desulfuromonadaceae	0.012357	0.01448	0.004181
195	Grab Sample	Paludibacteraceae	0.012100	0.01156	0.003336
438	Liquid Unstrained	Rhizobiaceae	0.011973	0.01288	0.004553
465	Solid	Akkermansiaceae	0.011909	0.00862	0.002487
503	Solid	Enterobacteriaceae	0.011871	0.01258	0.003631
261	Liquid Strained	Coriobacteriales_Incertae_Sedis	0.011861	0.01745	0.005038
504	Solid	Enterococcaceae	0.011840	0.01326	0.003828
554	Solid	Rhodobacteraceae	0.011757	0.03730	0.010766
375	Liquid Unstrained	COB_P4-1_termite_group	0.011549	0.02044	0.007225
576	Stomach Tube	0319-6G20	0.011458	0.01144	0.003302
215	Grab Sample	Sphingobacteriaceae	0.011142	0.01291	0.003728
690	Stomach Tube	Xanthomonadaceae	0.011051	0.01697	0.004898
235	Liquid Strained	Akkermansiaceae	0.010743	0.02096	0.006049
268	Liquid Strained	Devosiaceae	0.010652	0.01544	0.004458
223	Grab Sample	Syntrophomonadaceae	0.010589	0.01446	0.004173
634	Stomach Tube	Leuconostocaceae	0.010566	0.01540	0.004446
206	Grab Sample	Pseudomonadaceae	0.010421	0.01179	0.003403
667	Stomach Tube	Puniceicoccaceae	0.010249	0.02161	0.006239
228	Grab Sample	Victivallaceae	0.010203	0.01729	0.004990
605	Stomach Tube	COB_P4-1_termite_group	0.010136	0.01922	0.005548
81	Feces	Paracaedibacteraceae	0.010107	0.01009	0.002914
389	Liquid Unstrained	Enterococcaceae	0.009852	0.01506	0.005324
139	Grab Sample	Caulobacteraceae	0.009847	0.01328	0.003834
310	Liquid Strained	Paludibacteraceae	0.009671	0.01383	0.003994
274	Liquid Strained	Enterococcaceae	0.009554	0.01604	0.004630
552	Solid	Puniceicoccaceae	0.009533	0.01480	0.004272
191	Grab Sample	Oligoflexaceae	0.009434	0.01077	0.003110
306	Liquid Strained	Oligoflexaceae	0.009407	0.01333	0.003848
212	Grab Sample	Saccharimonadaceae	0.009296	0.01492	0.004306
324	Liquid Strained	Rhodobacteraceae	0.009238	0.01977	0.005706
421	Liquid Unstrained	Oligoflexaceae	0.009093	0.01400	0.004949
679	Stomach Tube	Staphylococcaceae	0.008935	0.01114	0.003215
413	Liquid Unstrained	Micrococcaceae	0.008915	0.00833	0.002947
460	Liquid Unstrained	Xanthomonadaceae	0.008705	0.01069	0.003781
31	Feces	Coriobacteriales_Incertae_Sedis	0.008646	0.01039	0.003000
92	Feces	Puniceicoccaceae	0.008564	0.01106	0.003192
93	Feces	Rhizobiaceae	0.008527	0.01238	0.003574
189	Grab Sample	Nocardiaceae	0.008524	0.01372	0.003960
433	Liquid Unstrained	Planococcaceae	0.008516	0.00977	0.003454
580	Stomach Tube	Akkermansiaceae	0.008449	0.01822	0.005260
551	Solid	Pseudomonadaceae	0.008411	0.01293	0.003731
439	Liquid Unstrained	Rhodobacteraceae	0.008172	0.02311	0.008172
224	Grab Sample	Tannerellaceae	0.008100	0.01354	0.003910
684	Stomach Tube	Tannerellaceae	0.008024	0.01124	0.003245
442	Liquid Unstrained	Saccharimonadaceae	0.007933	0.01167	0.004128
489	Solid	Clostridiales_vadinBB60_group	0.007843	0.01064	0.003071
536	Solid	Oligoflexaceae	0.007744	0.01022	0.002951
276	Liquid Strained	Eubacteriaceae	0.007682	0.00900	0.002599
519	Solid	Leuconostocaceae	0.007665	0.01402	0.004047
367	Liquid Unstrained	Cardiobacteriaceae	0.007579	0.01131	0.004000
43	Feces	Enterobacteriaceae	0.007410	0.01018	0.002940
636	Stomach Tube	Marinifilaceae	0.007326	0.01163	0.003356
569	Solid	Tannerellaceae	0.007273	0.00958	0.002766
643	Stomach Tube	Micrococcaceae	0.007272	0.01320	0.003809
495	Solid	Desulfobulbaceae	0.007171	0.00908	0.002621
364	Liquid Unstrained	Bifidobacteriaceae	0.007158	0.00831	0.002938
106	Feces	Succinivibrionaceae	0.007032	0.01058	0.003054
137	Grab Sample	Cardiobacteriaceae	0.006916	0.01109	0.003202
579	Stomach Tube	Aerococcaceae	0.006833	0.01062	0.003066
481	Solid	Campylobacteraceae	0.006831	0.00938	0.002708
560	Solid	Sphingobacteriaceae	0.006648	0.00984	0.002841
230	Grab Sample	Xanthomonadaceae	0.006581	0.01284	0.003705
683	Stomach Tube	Syntrophomonadaceae	0.006567	0.01018	0.002939
120	Grab Sample	Akkermansiaceae	0.006546	0.01421	0.004101
366	Liquid Unstrained	Campylobacteraceae	0.006356	0.00957	0.003384
73	Feces	Nitrosomonadaceae	0.006290	0.01090	0.003147
383	Liquid Unstrained	Devosiaceae	0.006279	0.00893	0.003156
673	Stomach Tube	Sanguibacteraceae	0.006265	0.00960	0.002771
116	Grab Sample	0319-6G20	0.006238	0.00950	0.002741
454	Liquid Unstrained	Tannerellaceae	0.006024	0.00927	0.003277
174	Grab Sample	Leuconostocaceae	0.006018	0.00931	0.002688
150	Grab Sample	Desulfobulbaceae	0.005998	0.00894	0.002582
282	Liquid Strained	Fusobacteriaceae	0.005850	0.00960	0.002771
573	Solid	Victivallaceae	0.005835	0.00943	0.002721
598	Stomach Tube	Carnobacteriaceae	0.005834	0.01105	0.003190
564	Solid	Staphylococcaceae	0.005711	0.00915	0.002642
312	Liquid Strained	Pasteurellaceae	0.005474	0.00828	0.002390
405	Liquid Unstrained	M2PB4-65_termite_group	0.005428	0.00770	0.002722
397	Liquid Unstrained	Fusobacteriaceae	0.005345	0.01225	0.004331
558	Solid	Sanguibacteraceae	0.005328	0.01039	0.003000
260	Liquid Strained	COB_P4-1_termite_group	0.005313	0.01142	0.003296
362	Liquid Unstrained	Beijerinckiaceae	0.005180	0.00800	0.002830
534	Solid	Nocardiaceae	0.005171	0.00857	0.002473
294	Liquid Strained	Methanocorpusculaceae	0.005139	0.00789	0.002277
417	Liquid Unstrained	Neisseriaceae	0.004997	0.00765	0.002704
419	Liquid Unstrained	Nocardiaceae	0.004994	0.00961	0.003397
339	Liquid Strained	Tannerellaceae	0.004955	0.01071	0.003093
484	Solid	Caulobacteraceae	0.004837	0.00800	0.002310
639	Stomach Tube	Methanocorpusculaceae	0.004764	0.00910	0.002626
247	Liquid Strained	Beijerinckiaceae	0.004646	0.00716	0.002066
12	Feces	Bacteroidales_BS11_gut_group	0.004608	0.00728	0.002101
327	Liquid Strained	Saccharimonadaceae	0.004565	0.00970	0.002799
453	Liquid Unstrained	Syntrophomonadaceae	0.004527	0.00854	0.003018
619	Stomach Tube	Enterococcaceae	0.004474	0.00879	0.002538
427	Liquid Unstrained	Pasteurellaceae	0.004470	0.00619	0.002188
499	Solid	Dysgonomonadaceae	0.004465	0.01358	0.003919
184	Grab Sample	Moraxellaceae	0.004450	0.01144	0.003302
443	Liquid Unstrained	Sanguibacteraceae	0.004430	0.00832	0.002943
65	Feces	Methanomethylophilaceae	0.004428	0.00972	0.002806
197	Grab Sample	Pasteurellaceae	0.004255	0.00774	0.002233
209	Grab Sample	Rhodobacteraceae	0.004225	0.00780	0.002252
207	Grab Sample	Puniceicoccaceae	0.004219	0.00768	0.002218
599	Stomach Tube	Caulobacteraceae	0.004160	0.00807	0.002330
479	Solid	Bifidobacteriaceae	0.004095	0.00831	0.002398
384	Liquid Unstrained	Dysgonomonadaceae	0.004086	0.01156	0.004086
44	Feces	Enterococcaceae	0.004080	0.00671	0.001937
592	Stomach Tube	Beijerinckiaceae	0.003940	0.00739	0.002133
461	Solid	0319-6G20	0.003940	0.00608	0.001755
159	Grab Sample	Enterococcaceae	0.003925	0.00723	0.002086
470	Solid	Bacteriovoracaceae	0.003837	0.00739	0.002132
557	Solid	Saccharimonadaceae	0.003777	0.00745	0.002152
449	Liquid Unstrained	Staphylococcaceae	0.003708	0.00781	0.002761
252	Liquid Strained	Cardiobacteriaceae	0.003585	0.00582	0.001680
404	Liquid Unstrained	Leuconostocaceae	0.003440	0.00641	0.002266
302	Liquid Strained	Neisseriaceae	0.003374	0.00613	0.001770
249	Liquid Strained	Bifidobacteriaceae	0.003305	0.00617	0.001781
67	Feces	Microbacteriaceae	0.003283	0.00643	0.001855
32	Feces	Corynebacteriaceae	0.003280	0.00491	0.001417
512	Solid	Fusobacteriaceae	0.003275	0.00490	0.001414
112	Feces	Veillonellaceae	0.003185	0.00592	0.001708
338	Liquid Strained	Syntrophomonadaceae	0.003165	0.00821	0.002370
239	Liquid Strained	Bacillaceae	0.003149	0.00771	0.002227
136	Grab Sample	Campylobacteraceae	0.003135	0.00778	0.002246
524	Solid	Methanocorpusculaceae	0.003118	0.00475	0.001372
635	Stomach Tube	M2PB4-65_termite_group	0.003070	0.00769	0.002219
234	Liquid Strained	Aerococcaceae	0.003042	0.00810	0.002338
298	Liquid Strained	Micrococcaceae	0.003002	0.00797	0.002300
218	Grab Sample	Spirosomaceae	0.002993	0.00702	0.002026
409	Liquid Unstrained	Methanocorpusculaceae	0.002976	0.00577	0.002039
213	Grab Sample	Sanguibacteraceae	0.002882	0.00678	0.001956
340	Liquid Strained	Terasakiellaceae	0.002859	0.00857	0.002473
125	Grab Sample	Bacteriovoracaceae	0.002827	0.00666	0.001921
17	Feces	Beijerinckiaceae	0.002809	0.00542	0.001564
594	Stomach Tube	Bifidobacteriaceae	0.002795	0.00507	0.001463
318	Liquid Strained	Planococcaceae	0.002769	0.00658	0.001901
334	Liquid Strained	Staphylococcaceae	0.002763	0.00649	0.001874
52	Feces	Fusobacteriaceae	0.002757	0.00500	0.001443
203	Grab Sample	Planococcaceae	0.002692	0.00932	0.002692
97	Feces	Saccharimonadaceae	0.002640	0.00482	0.001393
477	Solid	Beijerinckiaceae	0.002619	0.00478	0.001381
478	Solid	Beutenbergiaceae	0.002500	0.00689	0.001989
253	Liquid Strained	Carnobacteriaceae	0.002454	0.00850	0.002454
288	Liquid Strained	Leptotrichiaceae	0.002454	0.00850	0.002454
434	Liquid Unstrained	Porphyromonadaceae	0.002452	0.00458	0.001618
548	Solid	Planococcaceae	0.002440	0.00622	0.001795
132	Grab Sample	Beijerinckiaceae	0.002372	0.00558	0.001611
240	Liquid Strained	Bacteriovoracaceae	0.002319	0.00547	0.001578
448	Liquid Unstrained	Spirosomaceae	0.001968	0.00557	0.001968
33	Feces	Deferribacteraceae	0.001954	0.00677	0.001954
100	Feces	Sphingobacteriaceae	0.001954	0.00677	0.001954
549	Solid	Porphyromonadaceae	0.001854	0.00477	0.001378
539	Solid	p-2534-18B5_gut_group	0.001850	0.00432	0.001248
514	Solid	Hymenobacteraceae	0.001800	0.00421	0.001215
575	Solid	Xanthomonadaceae	0.001800	0.00421	0.001215
255	Liquid Strained	Cellvibrionaceae	0.001620	0.00437	0.001263
119	Grab Sample	Aerococcaceae	0.001591	0.00551	0.001591
167	Grab Sample	Fusobacteriaceae	0.001591	0.00551	0.001591
528	Solid	Micrococcaceae	0.001587	0.00372	0.001074
124	Grab Sample	Bacillaceae	0.001579	0.00547	0.001579
173	Grab Sample	Leptotrichiaceae	0.001579	0.00547	0.001579
179	Grab Sample	Methanocorpusculaceae	0.001579	0.00547	0.001579
399	Liquid Unstrained	Hymenobacteraceae	0.001554	0.00440	0.001554
455	Liquid Unstrained	Terasakiellaceae	0.001554	0.00440	0.001554
459	Liquid Unstrained	Weeksellaceae	0.001554	0.00440	0.001554
482	Solid	Cardiobacteriaceae	0.001517	0.00372	0.001075
333	Liquid Strained	Spirosomaceae	0.001507	0.00522	0.001507
305	Liquid Strained	Nocardioidaceae	0.001501	0.00398	0.001150
104	Feces	Staphylococcaceae	0.001454	0.00504	0.001454
483	Solid	Carnobacteriaceae	0.001437	0.00348	0.001006
74	Feces	Nocardiaceae	0.001411	0.00330	0.000952
254	Liquid Strained	Caulobacteraceae	0.001395	0.00364	0.001051
304	Liquid Strained	Nocardiaceae	0.001395	0.00364	0.001051
77	Feces	Oligosphaeraceae	0.001367	0.00474	0.001367
26	Feces	Chitinophagaceae	0.001357	0.00470	0.001357
101	Feces	Sphingomonadaceae	0.001357	0.00470	0.001357
190	Grab Sample	Nocardioidaceae	0.001291	0.00447	0.001291
600	Stomach Tube	Cellvibrionaceae	0.001285	0.00445	0.001285
650	Stomach Tube	Nocardioidaceae	0.001285	0.00445	0.001285
290	Liquid Strained	M2PB4-65_termite_group	0.001239	0.00429	0.001239
328	Liquid Strained	Sanguibacteraceae	0.001239	0.00429	0.001239
593	Stomach Tube	Beutenbergiaceae	0.001196	0.00414	0.001196
396	Liquid Unstrained	Flavobacteriaceae	0.001090	0.00308	0.001090
400	Liquid Unstrained	Kineosporiaceae	0.001090	0.00308	0.001090
133	Grab Sample	Beutenbergiaceae	0.001054	0.00365	0.001054
138	Grab Sample	Carnobacteriaceae	0.001054	0.00365	0.001054
204	Grab Sample	Porphyromonadaceae	0.001054	0.00365	0.001054
219	Grab Sample	Staphylococcaceae	0.001054	0.00365	0.001054
296	Liquid Strained	Methanosarcinaceae	0.001015	0.00351	0.001015
319	Liquid Strained	Porphyromonadaceae	0.001015	0.00351	0.001015
674	Stomach Tube	Solirubrobacteraceae	0.000993	0.00344	0.000993
349	Liquid Unstrained	Aerococcaceae	0.000984	0.00278	0.000984
369	Liquid Unstrained	Caulobacteraceae	0.000984	0.00278	0.000984
370	Liquid Unstrained	Cellvibrionaceae	0.000984	0.00278	0.000984
48	Feces	Family_XI	0.000977	0.00339	0.000977
42	Feces	Endomicrobiaceae	0.000968	0.00335	0.000968
98	Feces	Sanguibacteraceae	0.000945	0.00327	0.000945
91	Feces	Pseudomonadaceae	0.000930	0.00322	0.000930
115	Feces	Xanthomonadaceae	0.000930	0.00322	0.000930
486	Solid	Chitinophagaceae	0.000853	0.00296	0.000853
9	Feces	Bacillaceae	0.000844	0.00292	0.000844
68	Feces	Micrococcaceae	0.000844	0.00292	0.000844
72	Feces	Neisseriaceae	0.000844	0.00292	0.000844
82	Feces	Pasteurellaceae	0.000844	0.00292	0.000844
464	Solid	Aerococcaceae	0.000826	0.00286	0.000826
469	Solid	Bacillaceae	0.000826	0.00286	0.000826
526	Solid	Methanosarcinaceae	0.000826	0.00286	0.000826
284	Liquid Strained	Hymenobacteraceae	0.000762	0.00264	0.000762
309	Liquid Strained	p-2534-18B5_gut_group	0.000762	0.00264	0.000762
38	Feces	Devosiaceae	0.000727	0.00252	0.000727
107	Feces	Synergistaceae	0.000727	0.00252	0.000727
54	Feces	Hymenobacteraceae	0.000684	0.00237	0.000684
62	Feces	Marinilabiliaceae	0.000684	0.00237	0.000684
76	Feces	Oligoflexaceae	0.000684	0.00237	0.000684
570	Solid	Terasakiellaceae	0.000650	0.00225	0.000650
542	Solid	Pasteurellaceae	0.000534	0.00185	0.000534
563	Solid	Spirosomaceae	0.000534	0.00185	0.000534
1	Feces	0319-6G20	0.000000	0.00000	0.000000
4	Feces	Aerococcaceae	0.000000	0.00000	0.000000
10	Feces	Bacteriovoracaceae	0.000000	0.00000	0.000000
15	Feces	Bacteroidetes_BD2-2	0.000000	0.00000	0.000000
18	Feces	Beutenbergiaceae	0.000000	0.00000	0.000000
22	Feces	Cardiobacteriaceae	0.000000	0.00000	0.000000
23	Feces	Carnobacteriaceae	0.000000	0.00000	0.000000
24	Feces	Caulobacteraceae	0.000000	0.00000	0.000000
25	Feces	Cellvibrionaceae	0.000000	0.00000	0.000000
30	Feces	COB_P4-1_termite_group	0.000000	0.00000	0.000000
35	Feces	Desulfobulbaceae	0.000000	0.00000	0.000000
37	Feces	Desulfuromonadaceae	0.000000	0.00000	0.000000
39	Feces	Dysgonomonadaceae	0.000000	0.00000	0.000000
51	Feces	Flavobacteriaceae	0.000000	0.00000	0.000000
55	Feces	Kineosporiaceae	0.000000	0.00000	0.000000
58	Feces	Leptotrichiaceae	0.000000	0.00000	0.000000
59	Feces	Leuconostocaceae	0.000000	0.00000	0.000000
60	Feces	M2PB4-65_termite_group	0.000000	0.00000	0.000000
66	Feces	Methanosarcinaceae	0.000000	0.00000	0.000000
69	Feces	Moraxellaceae	0.000000	0.00000	0.000000
71	Feces	Mycoplasmataceae	0.000000	0.00000	0.000000
75	Feces	Nocardioidaceae	0.000000	0.00000	0.000000
83	Feces	Pedosphaeraceae	0.000000	0.00000	0.000000
84	Feces	PeH15	0.000000	0.00000	0.000000
89	Feces	Porphyromonadaceae	0.000000	0.00000	0.000000
94	Feces	Rhodobacteraceae	0.000000	0.00000	0.000000
99	Feces	Solirubrobacteraceae	0.000000	0.00000	0.000000
103	Feces	Spirosomaceae	0.000000	0.00000	0.000000
108	Feces	Syntrophomonadaceae	0.000000	0.00000	0.000000
114	Feces	Weeksellaceae	0.000000	0.00000	0.000000
117	Grab Sample	Acetobacteraceae	0.000000	0.00000	0.000000
131	Grab Sample	Barnesiellaceae	0.000000	0.00000	0.000000
134	Grab Sample	Bifidobacteriaceae	0.000000	0.00000	0.000000
140	Grab Sample	Cellvibrionaceae	0.000000	0.00000	0.000000
141	Grab Sample	Chitinophagaceae	0.000000	0.00000	0.000000
148	Grab Sample	Deferribacteraceae	0.000000	0.00000	0.000000
154	Grab Sample	Dysgonomonadaceae	0.000000	0.00000	0.000000
166	Grab Sample	Flavobacteriaceae	0.000000	0.00000	0.000000
168	Grab Sample	GZKB124	0.000000	0.00000	0.000000
169	Grab Sample	Hymenobacteraceae	0.000000	0.00000	0.000000
170	Grab Sample	Kineosporiaceae	0.000000	0.00000	0.000000
181	Grab Sample	Methanosarcinaceae	0.000000	0.00000	0.000000
183	Grab Sample	Micrococcaceae	0.000000	0.00000	0.000000
187	Grab Sample	Neisseriaceae	0.000000	0.00000	0.000000
188	Grab Sample	Nitrosomonadaceae	0.000000	0.00000	0.000000
192	Grab Sample	Oligosphaeraceae	0.000000	0.00000	0.000000
194	Grab Sample	p-2534-18B5_gut_group	0.000000	0.00000	0.000000
214	Grab Sample	Solirubrobacteraceae	0.000000	0.00000	0.000000
225	Grab Sample	Terasakiellaceae	0.000000	0.00000	0.000000
229	Grab Sample	Weeksellaceae	0.000000	0.00000	0.000000
232	Liquid Strained	Acetobacteraceae	0.000000	0.00000	0.000000
246	Liquid Strained	Barnesiellaceae	0.000000	0.00000	0.000000
248	Liquid Strained	Beutenbergiaceae	0.000000	0.00000	0.000000
256	Liquid Strained	Chitinophagaceae	0.000000	0.00000	0.000000
263	Liquid Strained	Deferribacteraceae	0.000000	0.00000	0.000000
269	Liquid Strained	Dysgonomonadaceae	0.000000	0.00000	0.000000
281	Liquid Strained	Flavobacteriaceae	0.000000	0.00000	0.000000
283	Liquid Strained	GZKB124	0.000000	0.00000	0.000000
285	Liquid Strained	Kineosporiaceae	0.000000	0.00000	0.000000
303	Liquid Strained	Nitrosomonadaceae	0.000000	0.00000	0.000000
307	Liquid Strained	Oligosphaeraceae	0.000000	0.00000	0.000000
329	Liquid Strained	Solirubrobacteraceae	0.000000	0.00000	0.000000
344	Liquid Strained	Weeksellaceae	0.000000	0.00000	0.000000
347	Liquid Unstrained	Acetobacteraceae	0.000000	0.00000	0.000000
354	Liquid Unstrained	Bacillaceae	0.000000	0.00000	0.000000
355	Liquid Unstrained	Bacteriovoracaceae	0.000000	0.00000	0.000000
361	Liquid Unstrained	Barnesiellaceae	0.000000	0.00000	0.000000
363	Liquid Unstrained	Beutenbergiaceae	0.000000	0.00000	0.000000
368	Liquid Unstrained	Carnobacteriaceae	0.000000	0.00000	0.000000
371	Liquid Unstrained	Chitinophagaceae	0.000000	0.00000	0.000000
378	Liquid Unstrained	Deferribacteraceae	0.000000	0.00000	0.000000
398	Liquid Unstrained	GZKB124	0.000000	0.00000	0.000000
403	Liquid Unstrained	Leptotrichiaceae	0.000000	0.00000	0.000000
411	Liquid Unstrained	Methanosarcinaceae	0.000000	0.00000	0.000000
418	Liquid Unstrained	Nitrosomonadaceae	0.000000	0.00000	0.000000
420	Liquid Unstrained	Nocardioidaceae	0.000000	0.00000	0.000000
422	Liquid Unstrained	Oligosphaeraceae	0.000000	0.00000	0.000000
424	Liquid Unstrained	p-2534-18B5_gut_group	0.000000	0.00000	0.000000
444	Liquid Unstrained	Solirubrobacteraceae	0.000000	0.00000	0.000000
462	Solid	Acetobacteraceae	0.000000	0.00000	0.000000
476	Solid	Barnesiellaceae	0.000000	0.00000	0.000000
485	Solid	Cellvibrionaceae	0.000000	0.00000	0.000000
493	Solid	Deferribacteraceae	0.000000	0.00000	0.000000
511	Solid	Flavobacteriaceae	0.000000	0.00000	0.000000
513	Solid	GZKB124	0.000000	0.00000	0.000000
515	Solid	Kineosporiaceae	0.000000	0.00000	0.000000
518	Solid	Leptotrichiaceae	0.000000	0.00000	0.000000
532	Solid	Neisseriaceae	0.000000	0.00000	0.000000
533	Solid	Nitrosomonadaceae	0.000000	0.00000	0.000000
535	Solid	Nocardioidaceae	0.000000	0.00000	0.000000
537	Solid	Oligosphaeraceae	0.000000	0.00000	0.000000
559	Solid	Solirubrobacteraceae	0.000000	0.00000	0.000000
574	Solid	Weeksellaceae	0.000000	0.00000	0.000000
577	Stomach Tube	Acetobacteraceae	0.000000	0.00000	0.000000
585	Stomach Tube	Bacteriovoracaceae	0.000000	0.00000	0.000000
591	Stomach Tube	Barnesiellaceae	0.000000	0.00000	0.000000
601	Stomach Tube	Chitinophagaceae	0.000000	0.00000	0.000000
608	Stomach Tube	Deferribacteraceae	0.000000	0.00000	0.000000
614	Stomach Tube	Dysgonomonadaceae	0.000000	0.00000	0.000000
626	Stomach Tube	Flavobacteriaceae	0.000000	0.00000	0.000000
628	Stomach Tube	GZKB124	0.000000	0.00000	0.000000
629	Stomach Tube	Hymenobacteraceae	0.000000	0.00000	0.000000
630	Stomach Tube	Kineosporiaceae	0.000000	0.00000	0.000000
641	Stomach Tube	Methanosarcinaceae	0.000000	0.00000	0.000000
648	Stomach Tube	Nitrosomonadaceae	0.000000	0.00000	0.000000
652	Stomach Tube	Oligosphaeraceae	0.000000	0.00000	0.000000
654	Stomach Tube	p-2534-18B5_gut_group	0.000000	0.00000	0.000000
669	Stomach Tube	Rhodobacteraceae	0.000000	0.00000	0.000000
678	Stomach Tube	Spirosomaceae	0.000000	0.00000	0.000000
685	Stomach Tube	Terasakiellaceae	0.000000	0.00000	0.000000
689	Stomach Tube	Weeksellaceae	0.000000	0.00000	0.000000

These are the families found in all samples sorted by decending order of mean relative abundance. Next we will graph out some of the different fam based on their abundance ranges.

We will have a closer look at the familes present in fecal samples.

These are the relative abundance of families found in fecal samples. Next we will graph out these families.

Intially, we can see that there is more Bacteroidaceae and Peptostreptococcaceae in fecal samples compared to rumen samples.

	Sample_Type	Family	mean	sd	sem
1	Feces	Bacteroidaceae	7.4037510	0.8711443	0.2514777
14	Grab Sample	Bacteroidaceae	0.0355318	0.0298742	0.0086239
27	Liquid Strained	Bacteroidaceae	0.0376197	0.0385991	0.0111426
40	Liquid Unstrained	Bacteroidaceae	0.0499720	0.0397877	0.0140671
53	Solid	Bacteroidaceae	0.0275221	0.0236625	0.0068308
66	Stomach Tube	Bacteroidaceae	0.0710867	0.1147546	0.0331268

	Sample_Type	Family	mean	sd	sem
8	Feces	Peptostreptococcaceae	2.8945224	0.8990991	0.2595475
21	Grab Sample	Peptostreptococcaceae	0.0273192	0.0178096	0.0051412
34	Liquid Strained	Peptostreptococcaceae	0.0365307	0.0322717	0.0093160
47	Liquid Unstrained	Peptostreptococcaceae	0.0322039	0.0175574	0.0062075
60	Solid	Peptostreptococcaceae	0.0327935	0.0206118	0.0059501
73	Stomach Tube	Peptostreptococcaceae	0.0435303	0.0159367	0.0046005

Conversely, there is more Veillonellaceae and Fibrobacteraceae in rumen samples compared to feces.

	Sample_Type	Family	mean	sd	sem
13	Feces	Veillonellaceae	0.0031847	0.0059171	0.0017081
26	Grab Sample	Veillonellaceae	0.7480463	0.1859221	0.0536711
39	Liquid Strained	Veillonellaceae	2.1133656	0.5698565	0.1645034
52	Liquid Unstrained	Veillonellaceae	1.5589519	0.8019100	0.2835180
65	Solid	Veillonellaceae	0.3685489	0.1024515	0.0295752
78	Stomach Tube	Veillonellaceae	0.6770020	0.4122323	0.1190012

	Sample_Type	Family	mean	sd	sem
5	Feces	Fibrobacteraceae	0.0186986	0.0180463	0.0052095
18	Grab Sample	Fibrobacteraceae	2.2866939	0.5464401	0.1577437
31	Liquid Strained	Fibrobacteraceae	2.0179385	0.7904481	0.2281827
44	Liquid Unstrained	Fibrobacteraceae	1.0178780	0.6578643	0.2325902
57	Solid	Fibrobacteraceae	1.5059297	0.6251762	0.1804728
70	Stomach Tube	Fibrobacteraceae	0.3770986	0.2593853	0.0748781

I will make an interactive bubble graph for the lower families

Next we are going to do some exploratory analysis of all sample types.

Archaea Populations

Now we will take a closer look at the Archeaon populations.

## [1] "These are the Classes in the Kingdom Archaea found in all sample types"

## [1] "Methanobacteria" "Thermoplasmata"  "Methanomicrobia"

## [1] "These are the Orders in the Kingdom Archaea found in all sample types"

## [1] "Methanobacteriales"      "Methanomassiliicoccales"
## [3] "Methanosarcinales"       "Methanomicrobiales"

## [1] "These are the Families in the Kingdom Archaea found in all sample types"

## [1] "Methanobacteriaceae"     "Methanomethylophilaceae"
## [3] "Methanosarcinaceae"      "Methanocorpusculaceae"

## [1] "These are the Genera in the Kingdom Archaea found in all sample types"

## [1] NA                                "Methanobrevibacter"             
## [3] "Methanosphaera"                  "Candidatus_Methanomethylophilus"
## [5] "Methanimicrococcus"              "Methanocorpusculum"

## [1] "These are the Species in the Kingdom Archaea found in all sample types"

## [1] NA

Looking at the relative abundances of archaeal genera in all samples.

Statistiscs for Abundance of Archaea Genera Across all Sample Types
	Sample_Type	Genus	mean	sd	sem
13	Liquid Strained	Methanobrevibacter	94.3304	2.7636	0.7978
18	Liquid Unstrained	Methanobrevibacter	91.9836	2.4326	0.8600
28	Stomach Tube	Methanobrevibacter	90.6458	2.8016	0.8088
8	Grab Sample	Methanobrevibacter	88.8381	3.0998	0.8948
23	Solid	Methanobrevibacter	87.1990	6.2745	1.8113
3	Feces	Methanobrevibacter	82.6272	13.4013	3.8686
4	Feces	Methanocorpusculum	13.8867	13.1204	3.7875
25	Solid	Methanosphaera	12.3900	5.6762	1.6386
10	Grab Sample	Methanosphaera	10.9553	3.0536	0.8815
30	Stomach Tube	Methanosphaera	9.0903	2.9570	0.8536
20	Liquid Unstrained	Methanosphaera	6.5510	2.5410	0.8984
15	Liquid Strained	Methanosphaera	5.1476	2.8505	0.8229
5	Feces	Methanosphaera	3.4862	4.7416	1.3688
16	Liquid Unstrained	Candidatus_Methanomethylophilus	1.2983	1.2264	0.4336
24	Solid	Methanocorpusculum	0.3248	0.7518	0.2170
11	Liquid Strained	Candidatus_Methanomethylophilus	0.2623	0.5970	0.1724
14	Liquid Strained	Methanocorpusculum	0.2010	0.3275	0.0945
19	Liquid Unstrained	Methanocorpusculum	0.1670	0.3097	0.1095
29	Stomach Tube	Methanocorpusculum	0.1416	0.2746	0.0793
6	Grab Sample	Candidatus_Methanomethylophilus	0.1366	0.4732	0.1366
26	Stomach Tube	Candidatus_Methanomethylophilus	0.1222	0.3278	0.0946
9	Grab Sample	Methanocorpusculum	0.0700	0.2426	0.0700
21	Solid	Candidatus_Methanomethylophilus	0.0678	0.2347	0.0678
12	Liquid Strained	Methanimicrococcus	0.0587	0.2033	0.0587
22	Solid	Methanimicrococcus	0.0184	0.0636	0.0184
1	Feces	Candidatus_Methanomethylophilus	0.0000	0.0000	0.0000
2	Feces	Methanimicrococcus	0.0000	0.0000	0.0000
7	Grab Sample	Methanimicrococcus	0.0000	0.0000	0.0000
17	Liquid Unstrained	Methanimicrococcus	0.0000	0.0000	0.0000
27	Stomach Tube	Methanimicrococcus	0.0000	0.0000	0.0000

Next we will check if there are certain archeal genera that are found in common between fecal and rumen samples. We will also look to see if there are differences between these two sample types.

## [1] "These taxa are found in both phyloseq objects"
## [1] "Methanobacteriaceae"   "Methanocorpusculaceae"
## [1] "These taxa are different between the phyloseq objects"
## [1] "Methanomethylophilaceae" "Methanosarcinaceae"

Next, we look at the relative abundances of genera in rumen samples.

Statistiscs for Abundance of Archaea Genera
	Sample_Type	Genus	mean	sd	sem
8	Liquid Strained	Methanobrevibacter	94.3304	2.7636	0.7978
13	Liquid Unstrained	Methanobrevibacter	91.9836	2.4326	0.8600
23	Stomach Tube	Methanobrevibacter	90.6458	2.8016	0.8088
3	Grab Sample	Methanobrevibacter	88.8381	3.0998	0.8948
18	Solid	Methanobrevibacter	87.1990	6.2745	1.8113
20	Solid	Methanosphaera	12.3900	5.6762	1.6386
5	Grab Sample	Methanosphaera	10.9553	3.0536	0.8815
25	Stomach Tube	Methanosphaera	9.0903	2.9570	0.8536
15	Liquid Unstrained	Methanosphaera	6.5510	2.5410	0.8984
10	Liquid Strained	Methanosphaera	5.1476	2.8505	0.8229
11	Liquid Unstrained	Candidatus_Methanomethylophilus	1.2983	1.2264	0.4336
19	Solid	Methanocorpusculum	0.3248	0.7518	0.2170
6	Liquid Strained	Candidatus_Methanomethylophilus	0.2623	0.5970	0.1724
9	Liquid Strained	Methanocorpusculum	0.2010	0.3275	0.0945
14	Liquid Unstrained	Methanocorpusculum	0.1670	0.3097	0.1095
24	Stomach Tube	Methanocorpusculum	0.1416	0.2746	0.0793
1	Grab Sample	Candidatus_Methanomethylophilus	0.1366	0.4732	0.1366
21	Stomach Tube	Candidatus_Methanomethylophilus	0.1222	0.3278	0.0946
4	Grab Sample	Methanocorpusculum	0.0700	0.2426	0.0700
16	Solid	Candidatus_Methanomethylophilus	0.0678	0.2347	0.0678
7	Liquid Strained	Methanimicrococcus	0.0587	0.2033	0.0587
17	Solid	Methanimicrococcus	0.0184	0.0636	0.0184
2	Grab Sample	Methanimicrococcus	0.0000	0.0000	0.0000
12	Liquid Unstrained	Methanimicrococcus	0.0000	0.0000	0.0000
22	Stomach Tube	Methanimicrococcus	0.0000	0.0000	0.0000

We will do the same for fecal samples.

Statistiscs for Abundance of Archaea Genera
Sample_Type	Genus	mean	sd	sem
Feces	Methanobrevibacter	82.63	13.40	3.87
Feces	Methanocorpusculum	13.89	13.12	3.79
Feces	Methanosphaera	3.49	4.74	1.37

Unsupervised exploratory analysis

Going to use log transformations for normalizing for library size during exploratory analysis. As this looks appropriate for the “tailed” data. For additional confirmation we could do a the same analysis on ranked values for abundance.

## Saving 7 x 5 in image

The fecal samples pull away from the other samples on the first axis. Liquid strained and unstrained samples move higher on the 2nd axis, but this difference is 1/5th that of the differences between fecal samples and all other samples. Overall, it appears that there is 2-3 “clusters”. Next we will ordinate unifrac distances which will take into account phylogenetic differeces in differences in samples.

From the eigenvalues we can see that 2 axis is appropriate for graphing, together explaining 86.7954988% of the variance between the samples.

This is Figure 3. We will calculate the gap statisitic to determine how many clusters are here.

The gap statistic strongly suggests at least three clusters, but makes another big jump at K=5 before the slope levels. So, K=5 it is. We had 6 sample types so this suggests 2 of the sample types are basically the same.

Now that we take into account phylogenetic information in the distance metric we see a similar clustering pattern as with the bray-curtis. However, now the difference between fecal and other samples on the 1st axis explain 66.5% of the variation. Also, although not quite as clean there still seems to be 3 “clusters”. If you didn’t have stomach tube samples this would be more clear. Grab sample and solid samples aren’t very different from each other.

For good measure we will look at the unweighted unifrac that puts more weight on rare species as well.

We’ll first let’s check on the eigenvalues.

The eigenvalues here show 2 axis are sufficient to capture most of the total variation.

This gives a similar pattern as the bray-curtis and weighted unifrac. Notice that less of the variation is explained in each axis with the unweighted (total 52.7%) versus the weighted unifrac. The fecal samples are clustered closer together than with the weighted unifrac. Again, we will look at the gap statistic.

Just as before, the gap statistic strongly suggests at least three clusters, but makes another big jump at K=5 before the slope levels. So, K=5 it is. We had 6 sample types so this suggests 2 of the sample types are basically the same.

Another way to comparing phylogentic differences is double principal coordinates analysis (DPCoA), which is a phylogenetic ordination method and that provides a biplot representation of both samples and taxonomic categories. The computational time for this is much longer than with the unifrac (i.e. Has to be run on a server).

The eigenvalues here show 2 axis are sufficient to capture most of the total variation.

We see again that the 1st axis corresponds to Rumen vs.fecal samples, while the 2nd axis distinguishes Liquid preparations vs those that get liquid and solid fractions. The biplot suggests that the 1st axis can be interpreted to say: samples that have larger scores on the first axis have a subset of taxa from Bacteroidetes and subset of Firmicutes that is different than rumen samples. Additionally, Liquid samples have more Bacteroidetes and less Firmicutes than other rumen sample types. Liquid strained samples are being pulled down on the 2nd axis by Kiritimatiellaeota and a subset of Bacteroidetes.

Again, I have made an interactive Version of this plot that is avaliable here.

Since Firmicutes and Bacteroidetes take up so much of the graph we want to know what other phyla can separate the sample types.

Again, I have made an interactive Version of this plot that is avaliable here.

Now that we have Firmicutes and Bacteroidetes gone we can see that feces are associated with Akkermansiaceae and isn’t associated with Kiritimatiellaeota, Chloroflexi, Fibrobacteraceae and Spirochaetaceae.

Shared ASVs between sample types.

Liquid unstrained samples have 510 ASVs in common. Liquid strained samples have 307 ASVs in common. Samples from feces have 441 ASVs in common with one another. Soild samples have 405 ASVs in common. Samples from a stomach tube have 255 ASVs in common. Grab samples have 319 ASVs in common.

Differential Abundance Testing

Corncob: Grab sample vs all other sample types

First we will look at how the “gold standard” grab sample compares to other sample types. We test all the taxa in our data to see if they are differentially-abundant. The differentialTest function will these tests on all taxa, while controlling the false discovery rate to account for multiple comparisons. Addtionally, it controls for differencs in library sizes.

We will take a broad view and look at phyla that are differentially abundant

Looking at the models from corncob.

## $Bacteria_Tenericutes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.32618    0.08935 -48.418  < 2e-16 ***
## Sample_TypeFeces             -0.32385    0.09904  -3.270 0.001844 ** 
## Sample_TypeStomach Tube       0.14483    0.09009   1.608 0.113558    
## Sample_TypeLiquid Strained    0.41839    0.08479   4.934 7.58e-06 ***
## Sample_TypeLiquid Unstrained  0.35318    0.09588   3.684 0.000519 ***
## Sample_TypeSolid             -0.20922    0.09627  -2.173 0.034002 *  
## CowIDCow_2477                 0.11394    0.07278   1.566 0.123058    
## CowIDCow_2549                 0.02563    0.07502   0.342 0.733939    
## CowIDCow_796                 -0.05018    0.07647  -0.656 0.514415    
## DayDay_7                      0.02400    0.06693   0.359 0.721206    
## DayDay_9                     -0.01661    0.06224  -0.267 0.790558    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -7.5406     0.2152  -35.04   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -307.82
## 
## $Bacteria_Kiritimatiellaeota
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.66083    0.14790 -31.514  < 2e-16 ***
## Sample_TypeFeces             -0.19514    0.18212  -1.071 0.288551    
## Sample_TypeStomach Tube       0.55100    0.15792   3.489 0.000951 ***
## Sample_TypeLiquid Strained    1.98774    0.13439  14.791  < 2e-16 ***
## Sample_TypeLiquid Unstrained  1.31125    0.15124   8.670 6.19e-12 ***
## Sample_TypeSolid             -0.15332    0.17998  -0.852 0.397920    
## CowIDCow_2477                 0.09767    0.09331   1.047 0.299717    
## CowIDCow_2549                -0.14153    0.09935  -1.425 0.159826    
## CowIDCow_796                 -0.29557    0.10239  -2.887 0.005520 ** 
## DayDay_7                      0.08338    0.09483   0.879 0.382986    
## DayDay_9                      0.36822    0.08184   4.499 3.49e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6.2890     0.1865  -33.72   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -349.59
## 
## $Bacteria_Verrucomicrobia
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -5.860455   0.145912 -40.164  < 2e-16 ***
## Sample_TypeFeces              1.340823   0.130015  10.313 1.48e-14 ***
## Sample_TypeStomach Tube       0.591455   0.144743   4.086 0.000141 ***
## Sample_TypeLiquid Strained    0.159528   0.156768   1.018 0.313242    
## Sample_TypeLiquid Unstrained  0.451235   0.161794   2.789 0.007212 ** 
## Sample_TypeSolid              0.052724   0.157616   0.335 0.739247    
## CowIDCow_2477                 0.248618   0.105124   2.365 0.021520 *  
## CowIDCow_2549                 0.169063   0.109513   1.544 0.128275    
## CowIDCow_796                  0.316604   0.104636   3.026 0.003741 ** 
## DayDay_7                     -0.027690   0.091791  -0.302 0.764025    
## DayDay_9                      0.005016   0.086490   0.058 0.953961    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -7.8166     0.2357  -33.16   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -266.88
## 
## $Bacteria_Epsilonbacteraeota
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -10.51920    0.75370 -13.957  < 2e-16 ***
## Sample_TypeFeces               2.59059    0.72991   3.549 0.000791 ***
## Sample_TypeStomach Tube        1.84208    0.77336   2.382 0.020646 *  
## Sample_TypeLiquid Strained     1.90205    0.76235   2.495 0.015572 *  
## Sample_TypeLiquid Unstrained   0.52436    0.87565   0.599 0.551702    
## Sample_TypeSolid               0.85753    0.80476   1.066 0.291193    
## CowIDCow_2477                  0.75178    0.28370   2.650 0.010444 *  
## CowIDCow_2549                 -0.07158    0.36864  -0.194 0.846743    
## CowIDCow_796                  -0.53520    0.40013  -1.338 0.186442    
## DayDay_7                      -0.53806    0.29915  -1.799 0.077466 .  
## DayDay_9                       0.07371    0.25463   0.289 0.773277    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -11.474      2.969  -3.865 0.000291 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -80.421
## 
## $Bacteria_Elusimicrobia
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -6.97333    0.20177 -34.561  < 2e-16 ***
## Sample_TypeFeces             -0.09038    0.22702  -0.398    0.692    
## Sample_TypeStomach Tube       0.34659    0.21366   1.622    0.110    
## Sample_TypeLiquid Strained    1.20583    0.18644   6.468 2.61e-08 ***
## Sample_TypeLiquid Unstrained  0.95436    0.20218   4.720 1.62e-05 ***
## Sample_TypeSolid              0.30858    0.20944   1.473    0.146    
## CowIDCow_2477                 0.58131    0.13758   4.225 8.88e-05 ***
## CowIDCow_2549                 0.03532    0.15654   0.226    0.822    
## CowIDCow_796                 -0.12122    0.16197  -0.748    0.457    
## DayDay_7                     -0.17256    0.13773  -1.253    0.215    
## DayDay_9                      0.17873    0.11616   1.539    0.130    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -8.4564     0.2785  -30.37   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -210.21
## 
## $Bacteria_Planctomycetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -6.95287    0.15019 -46.295  < 2e-16 ***
## Sample_TypeFeces              0.69873    0.14002   4.990  6.2e-06 ***
## Sample_TypeStomach Tube       0.28194    0.15811   1.783   0.0800 .  
## Sample_TypeLiquid Strained   -0.30166    0.17245  -1.749   0.0857 .  
## Sample_TypeLiquid Unstrained -0.06845    0.17834  -0.384   0.7026    
## Sample_TypeSolid              0.10523    0.15201   0.692   0.4916    
## CowIDCow_2477                -0.13631    0.11419  -1.194   0.2376    
## CowIDCow_2549                 0.07430    0.11610   0.640   0.5248    
## CowIDCow_796                  0.11625    0.11074   1.050   0.2984    
## DayDay_7                     -0.07950    0.10021  -0.793   0.4309    
## DayDay_9                     -0.03517    0.09700  -0.363   0.7183    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02      49.49  -0.364    0.717
## 
## 
## Log-likelihood: -163.02
## 
## $Bacteria_Patescibacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -5.22958    0.10429 -50.144  < 2e-16 ***
## Sample_TypeFeces             -4.33629    0.50006  -8.672 6.15e-12 ***
## Sample_TypeStomach Tube      -0.38750    0.11263  -3.440  0.00110 ** 
## Sample_TypeLiquid Strained   -0.06420    0.10112  -0.635  0.52807    
## Sample_TypeLiquid Unstrained  0.06616    0.11269   0.587  0.55949    
## Sample_TypeSolid              0.29885    0.09132   3.273  0.00183 ** 
## CowIDCow_2477                -0.13598    0.09056  -1.502  0.13884    
## CowIDCow_2549                -0.23319    0.09478  -2.460  0.01699 *  
## CowIDCow_796                  0.13796    0.08702   1.585  0.11850    
## DayDay_7                      0.17327    0.07951   2.179  0.03353 *  
## DayDay_9                     -0.06957    0.07835  -0.888  0.37837    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -8.738      0.343  -25.47   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -213.52
## 
## $Bacteria_Proteobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.34791    0.11118 -39.107  < 2e-16 ***
## Sample_TypeFeces             -0.41730    0.12915  -3.231 0.002068 ** 
## Sample_TypeStomach Tube       0.12531    0.11381   1.101 0.275561    
## Sample_TypeLiquid Strained    0.91226    0.09900   9.215 8.13e-13 ***
## Sample_TypeLiquid Unstrained  0.54359    0.11377   4.778 1.32e-05 ***
## Sample_TypeSolid             -0.03213    0.11691  -0.275 0.784479    
## CowIDCow_2477                 0.45601    0.08564   5.325 1.85e-06 ***
## CowIDCow_2549                 0.32237    0.08849   3.643 0.000591 ***
## CowIDCow_796                 -0.13856    0.09773  -1.418 0.161787    
## DayDay_7                     -0.13382    0.08325  -1.607 0.113582    
## DayDay_9                      0.23357    0.07003   3.335 0.001517 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6.7521     0.1918   -35.2   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -339.24
## 
## $Bacteria_Fusobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -9.40842    0.72991 -12.890  < 2e-16 ***
## Sample_TypeFeces              0.02635    0.91483   0.029 0.977121    
## Sample_TypeStomach Tube       3.80213    0.72825   5.221  2.7e-06 ***
## Sample_TypeLiquid Strained    0.66197    0.82281   0.805 0.424494    
## Sample_TypeLiquid Unstrained  0.62044    0.98151   0.632 0.529877    
## Sample_TypeSolid              0.42278    0.86887   0.487 0.628449    
## CowIDCow_2477                -0.79047    0.26869  -2.942 0.004737 ** 
## CowIDCow_2549                -0.88565    0.27579  -3.211 0.002190 ** 
## CowIDCow_796                 -0.55192    0.27870  -1.980 0.052587 .  
## DayDay_7                     -0.97230    0.24566  -3.958 0.000215 ***
## DayDay_9                     -1.00289    0.27730  -3.617 0.000641 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -10.465      1.562  -6.698 1.09e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -76.012
## 
## $Archaea_Euryarchaeota
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -3.36934    0.14166 -23.784  < 2e-16 ***
## Sample_TypeFeces             -1.37244    0.21409  -6.411 3.24e-08 ***
## Sample_TypeStomach Tube       0.27843    0.13998   1.989  0.05159 .  
## Sample_TypeLiquid Strained   -0.16155    0.15362  -1.052  0.29751    
## Sample_TypeLiquid Unstrained -0.23238    0.18171  -1.279  0.20623    
## Sample_TypeSolid              0.19658    0.14210   1.383  0.17205    
## CowIDCow_2477                -0.39646    0.13020  -3.045  0.00354 ** 
## CowIDCow_2549                -0.64312    0.14188  -4.533 3.11e-05 ***
## CowIDCow_796                  0.03754    0.11753   0.319  0.75060    
## DayDay_7                     -0.02151    0.11568  -0.186  0.85317    
## DayDay_9                     -0.09570    0.11006  -0.870  0.38826    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -5.6966     0.1806  -31.55   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -373.86
## 
## $Bacteria_Spirochaetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -3.60125    0.23700 -15.195  < 2e-16 ***
## Sample_TypeFeces             -1.53490    0.30187  -5.085 4.42e-06 ***
## Sample_TypeStomach Tube      -0.83674    0.26859  -3.115  0.00290 ** 
## Sample_TypeLiquid Strained   -0.16348    0.22976  -0.712  0.47971    
## Sample_TypeLiquid Unstrained -0.27352    0.27019  -1.012  0.31573    
## Sample_TypeSolid             -0.72480    0.25765  -2.813  0.00675 ** 
## CowIDCow_2477                 0.06750    0.22101   0.305  0.76119    
## CowIDCow_2549                 0.22085    0.22116   0.999  0.32230    
## CowIDCow_796                 -0.20800    0.23062  -0.902  0.37095    
## DayDay_7                      0.20597    0.20392   1.010  0.31680    
## DayDay_9                      0.08773    0.18761   0.468  0.64189    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -4.662      0.187  -24.94   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -386.64
## 
## $Bacteria_Lentisphaerae
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   -7.0354     0.2514 -27.987  < 2e-16 ***
## Sample_TypeFeces               0.8589     0.2691   3.191  0.00232 ** 
## Sample_TypeStomach Tube        1.5299     0.2498   6.125 9.52e-08 ***
## Sample_TypeLiquid Strained     2.0078     0.2404   8.353 2.04e-11 ***
## Sample_TypeLiquid Unstrained   1.9137     0.2545   7.519 4.79e-10 ***
## Sample_TypeSolid              -0.1782     0.3163  -0.563  0.57539    
## CowIDCow_2477                  0.2979     0.1344   2.217  0.03073 *  
## CowIDCow_2549                 -0.3844     0.1600  -2.403  0.01959 *  
## CowIDCow_796                  -0.3786     0.1589  -2.383  0.02061 *  
## DayDay_7                       0.1512     0.1390   1.088  0.28111    
## DayDay_9                       0.2184     0.1219   1.791  0.07865 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -7.593      0.225  -33.74   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -239.06
## 
## $Bacteria_Cyanobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -6.677072   0.203395 -32.828  < 2e-16 ***
## Sample_TypeFeces              1.084069   0.195841   5.535 8.55e-07 ***
## Sample_TypeStomach Tube       0.553285   0.216712   2.553   0.0134 *  
## Sample_TypeLiquid Strained    1.780932   0.185392   9.606 1.92e-13 ***
## Sample_TypeLiquid Unstrained  1.338819   0.204092   6.560 1.84e-08 ***
## Sample_TypeSolid             -0.487660   0.262533  -1.858   0.0685 .  
## CowIDCow_2477                 0.623051   0.120964   5.151 3.48e-06 ***
## CowIDCow_2549                -0.146135   0.144215  -1.013   0.3153    
## CowIDCow_796                  0.009669   0.138073   0.070   0.9444    
## DayDay_7                     -0.098718   0.119096  -0.829   0.4107    
## DayDay_9                      0.139419   0.103197   1.351   0.1821    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -7.7710     0.2329  -33.36   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -245.28
## 
## $Bacteria_Actinobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.37305    0.09241 -47.323  < 2e-16 ***
## Sample_TypeFeces             -0.99467    0.12296  -8.089 5.51e-11 ***
## Sample_TypeStomach Tube       0.37822    0.08711   4.342 5.98e-05 ***
## Sample_TypeLiquid Strained   -0.47105    0.10640  -4.427 4.47e-05 ***
## Sample_TypeLiquid Unstrained -0.14511    0.11206  -1.295    0.201    
## Sample_TypeSolid              0.11323    0.09073   1.248    0.217    
## CowIDCow_2477                 0.06229    0.08059   0.773    0.443    
## CowIDCow_2549                -0.01023    0.08326  -0.123    0.903    
## CowIDCow_796                 -0.06658    0.08437  -0.789    0.433    
## DayDay_7                     -0.07041    0.07052  -0.998    0.322    
## DayDay_9                     -0.33301    0.07136  -4.666 1.95e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -7.758      0.228  -34.03   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -286.95
## 
## $Bacteria_Fibrobacteres
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -3.85541    0.12869 -29.960  < 2e-16 ***
## Sample_TypeFeces             -3.66382    0.34094 -10.746 3.16e-15 ***
## Sample_TypeStomach Tube      -1.79490    0.19964  -8.991 1.87e-12 ***
## Sample_TypeLiquid Strained   -0.20619    0.12115  -1.702 0.094304 .  
## Sample_TypeLiquid Unstrained -0.95051    0.17339  -5.482 1.04e-06 ***
## Sample_TypeSolid             -0.44792    0.12854  -3.485 0.000965 ***
## CowIDCow_2477                 0.20363    0.12806   1.590 0.117426    
## CowIDCow_2549                 0.04339    0.13403   0.324 0.747362    
## CowIDCow_796                 -0.06200    0.13730  -0.452 0.653342    
## DayDay_7                     -0.09475    0.12010  -0.789 0.433470    
## DayDay_9                      0.09135    0.11044   0.827 0.411705    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6.4614     0.2001  -32.28   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -297.24
## 
## $Bacteria_Chloroflexi
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -5.16680    0.08413 -61.413  < 2e-16 ***
## Sample_TypeFeces             -2.84256    0.21915 -12.971  < 2e-16 ***
## Sample_TypeStomach Tube       0.14863    0.08110   1.833  0.07217 .  
## Sample_TypeLiquid Strained   -0.29404    0.08904  -3.302  0.00167 ** 
## Sample_TypeLiquid Unstrained -0.01259    0.09335  -0.135  0.89320    
## Sample_TypeSolid              0.17696    0.07707   2.296  0.02544 *  
## CowIDCow_2477                 0.03086    0.07226   0.427  0.67099    
## CowIDCow_2549                -0.06050    0.07532  -0.803  0.42522    
## CowIDCow_796                  0.06224    0.07387   0.843  0.40307    
## DayDay_7                      0.08942    0.06434   1.390  0.17010    
## DayDay_9                     -0.04975    0.06268  -0.794  0.43073    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -9.3891     0.4459  -21.05   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -223.85
## 
## $Bacteria_Synergistetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -7.54350    0.19936 -37.839  < 2e-16 ***
## Sample_TypeFeces             -4.39512    1.00931  -4.355 5.73e-05 ***
## Sample_TypeStomach Tube      -0.36401    0.20607  -1.767  0.08276 .  
## Sample_TypeLiquid Strained   -0.51760    0.20678  -2.503  0.01526 *  
## Sample_TypeLiquid Unstrained -0.56557    0.22408  -2.524  0.01447 *  
## Sample_TypeSolid              0.46773    0.16073   2.910  0.00518 ** 
## CowIDCow_2477                 0.42127    0.16165   2.606  0.01171 *  
## CowIDCow_2549                 0.38915    0.16631   2.340  0.02288 *  
## CowIDCow_796                 -0.11407    0.18717  -0.609  0.54469    
## DayDay_7                      0.05518    0.14853   0.372  0.71167    
## DayDay_9                      0.35590    0.13760   2.586  0.01233 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02      67.71  -0.266    0.791
## 
## 
## Log-likelihood: -123.07
## 
## $Bacteria_Firmicutes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   0.690866   0.080250   8.609 7.78e-12 ***
## Sample_TypeFeces             -0.131144   0.082612  -1.587 0.118038    
## Sample_TypeStomach Tube       0.021783   0.083320   0.261 0.794714    
## Sample_TypeLiquid Strained   -0.847284   0.081895 -10.346 1.31e-14 ***
## Sample_TypeLiquid Unstrained -0.377057   0.092779  -4.064 0.000152 ***
## Sample_TypeSolid              0.122158   0.084022   1.454 0.151558    
## CowIDCow_2477                -0.131287   0.068888  -1.906 0.061814 .  
## CowIDCow_2549                -0.088555   0.069290  -1.278 0.206511    
## CowIDCow_796                 -0.007342   0.069413  -0.106 0.916143    
## DayDay_7                     -0.043941   0.062793  -0.700 0.486964    
## DayDay_9                     -0.093202   0.058245  -1.600 0.115187    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -4.6580     0.1732  -26.89   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -495.27
## 
## $Bacteria_Bacteroidetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -1.45985    0.07056 -20.690  < 2e-16 ***
## Sample_TypeFeces              0.63296    0.06994   9.051 1.49e-12 ***
## Sample_TypeStomach Tube       0.03734    0.07467   0.500    0.619    
## Sample_TypeLiquid Strained    0.68808    0.06974   9.867 7.42e-14 ***
## Sample_TypeLiquid Unstrained  0.35169    0.08093   4.345 5.91e-05 ***
## Sample_TypeSolid              0.01534    0.07479   0.205    0.838    
## CowIDCow_2477                 0.09105    0.05875   1.550    0.127    
## CowIDCow_2549                 0.09216    0.05881   1.567    0.123    
## CowIDCow_796                  0.08511    0.05861   1.452    0.152    
## DayDay_7                     -0.01002    0.05289  -0.189    0.850    
## DayDay_9                      0.03951    0.04918   0.803    0.425    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -5.2363     0.1756  -29.81   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -467.93

Next and collapse ASVs in the families and determine what families are differentially abundant.

This is a broad over view of the families that are significant differentially abundant in sample types. We will also dig down further and look at the genus and ASV level.

Phyla with Significant ASVs
Phylum	#Significant ASVs	Total ASVs	Percent Significant ASVs
Actinobacteria	23	96	23.958333
Bacteroidetes	56	1257	4.455052
Chloroflexi	15	39	38.461539
Cyanobacteria	6	65	9.230769
Elusimicrobia	3	16	18.750000
Euryarchaeota	16	44	36.363636
Fibrobacteres	8	39	20.512821
Firmicutes	540	3095	17.447496
Kiritimatiellaeota	17	180	9.444444
Lentisphaerae	3	31	9.677419
Patescibacteria	3	14	21.428571
Proteobacteria	11	219	5.022831
Spirochaetes	8	138	5.797101
Tenericutes	15	188	7.978723
Verrucomicrobia	1	35	2.857143
Deferribacteres	0	1	0.000000
Epsilonbacteraeota	0	2	0.000000
Fusobacteria	0	4	0.000000
Gemmatimonadetes	0	1	0.000000
Planctomycetes	0	15	0.000000
Synergistetes	0	6	0.000000

There are 725 significantly differentially abundant ASVs with p < 0.05. Most of these ASVs were from the phyla Firmicutes and Bacteroidetes, but that is in part due to them being the dominant ASVs in the data set. As a percentage of ASVs, Chloroflexi and Euryarchaeota played a large role in distinguish different sample types.

We will graph out the significantly different ASVs from these phylums. First, we look at signficantly differentially abundant ASVs Chloroflexi and Euryarchaeota.

Here we can see that the Euryarchaeota that are important for telling samples types apart are all methanogens. Feces has a strong negative effect on most of these methanogens (methogens are lower in feces). Interestingly, fecal samples have lower Flexilinea.

In addition, based on the DPCoA without Bacteroidetes and Firmicutes we can see that Actinobacteria and Spirochaetes also play and important role in distinguishing liquid strained and fecal from grab samples respectively.

Next we examine the different ASVs in the phylum Bacteroidetes and Firmicutes.

This is a graph of the significant differentially abundant ASVs in the phylum Bacteroidetes.

This is a graph of the significant differentially abundant ASVs in the phylum Firmicutes.

Now we will look further up the phylogenetic tree and collapse ASVs into genera and look for genera differentially abundnant.

There are 121 significantly differentially abundant genera with p < 0.05 and 113 with a p < 0.01. After running corncob 158 genera could not be fit with the model, but 134 were fit to the model.

Let’s extract the ASVs and their p-values.

Differentially Abundant Taxa
	p_value	ASV	Taxa
1	1.29e-03	ASV_1	Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group
2	1.29e-03	ASV_10	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans
3	1.29e-03	ASV_1006	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Candidatus_Soleaferrea
4	1.29e-03	ASV_1016	Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis
5	1.29e-03	ASV_103	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1
6	1.29e-03	ASV_105	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group
7	1.29e-03	ASV_1118	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_4
8	1.29e-03	ASV_1130	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018
9	1.29e-03	ASV_1132	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group
10	1.29e-03	ASV_1161	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006
11	1.29e-03	ASV_1169	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Syntrophococcus
12	1.29e-03	ASV_117	Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus
13	1.29e-03	ASV_120	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002
14	1.29e-03	ASV_1220	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_5
15	1.29e-03	ASV_1221	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium
16	1.29e-03	ASV_124	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group
18	1.29e-03	ASV_1366	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio
19	1.29e-03	ASV_1372	Bacteria_Fusobacteria_Fusobacteriia_Fusobacteriales_Fusobacteriaceae_Fusobacterium
20	1.29e-03	ASV_14	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium
21	1.29e-03	ASV_1403	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Howardella
22	1.29e-03	ASV_1434	Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae_Methanocorpusculum
23	1.29e-03	ASV_1440	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium
24	1.29e-03	ASV_145	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group
25	1.29e-03	ASV_149	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio
27	1.29e-03	ASV_16	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group
28	1.29e-03	ASV_168	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Turicibacter
29	1.29e-03	ASV_1682	Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1
30	1.29e-03	ASV_169	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-004
31	1.29e-03	ASV_172	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809
32	1.29e-03	ASV_176	Bacteria_Proteobacteria_Gammaproteobacteria_Pseudomonadales_Pseudomonadaceae_Pseudomonas
33	1.29e-03	ASV_183	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014
34	1.29e-03	ASV_184	Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera
35	1.29e-03	ASV_1915	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_FD2005
36	1.29e-03	ASV_192	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group
37	1.29e-03	ASV_199	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella
38	1.29e-03	ASV_2	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group
39	1.29e-03	ASV_20	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1
40	1.29e-03	ASV_201	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group
42	1.29e-03	ASV_2079	Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae_Campylobacter
43	1.29e-03	ASV_210	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10
44	1.29e-03	ASV_212	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010
48	1.29e-03	ASV_22	Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella
49	1.29e-03	ASV_2217	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae_Parabacteroides
50	1.29e-03	ASV_23	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1
53	1.29e-03	ASV_232	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1
54	1.29e-03	ASV_246	Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma
55	1.29e-03	ASV_247	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-009
56	1.29e-03	ASV_248	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group
57	1.29e-03	ASV_25	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio
58	1.29e-03	ASV_2540	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_Denitrobacterium
59	1.29e-03	ASV_26	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004
60	1.29e-03	ASV_267	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013
62	1.29e-03	ASV_29	Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_Treponema_2
63	1.29e-03	ASV_298	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax
65	1.29e-03	ASV_3	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005
66	1.29e-03	ASV_311	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella
67	1.29e-03	ASV_320	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10
68	1.29e-03	ASV_3270	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Caproiciproducens
69	1.29e-03	ASV_330	Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae_Akkermansia
70	1.29e-03	ASV_336	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_dgA-11_gut_group
72	1.29e-03	ASV_348	Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011
73	1.29e-03	ASV_357	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002
74	1.29e-03	ASV_36	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae_Bacteroides
76	1.29e-03	ASV_37	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter
77	1.29e-03	ASV_376	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group
78	1.29e-03	ASV_399	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_2
79	1.29e-03	ASV_4	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group
80	1.29e-03	ASV_409	Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea
81	1.29e-03	ASV_418	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium
82	1.29e-03	ASV_428	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia
83	1.29e-03	ASV_442	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Phascolarctobacterium
84	1.29e-03	ASV_450	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter
85	1.29e-03	ASV_457	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008
86	1.29e-03	ASV_462	Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium
87	1.29e-03	ASV_471	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium
88	1.29e-03	ASV_474	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001
89	1.29e-03	ASV_48	Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae_Romboutsia
90	1.29e-03	ASV_510	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Alloprevotella
93	1.29e-03	ASV_560	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6
94	1.29e-03	ASV_563	Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae_Candidatus_Endomicrobium
95	1.29e-03	ASV_57	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia
96	1.29e-03	ASV_60	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Alistipes
98	1.29e-03	ASV_622	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium
99	1.29e-03	ASV_636	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
100	1.29e-03	ASV_656	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter
101	1.29e-03	ASV_66	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum
102	1.29e-03	ASV_670	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Roseburia
103	1.29e-03	ASV_674	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera
104	1.29e-03	ASV_68	Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter
105	1.29e-03	ASV_7	Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter
106	1.29e-03	ASV_71	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2
107	1.29e-03	ASV_72	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001
108	1.29e-03	ASV_733	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
109	1.29e-03	ASV_757	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_1
110	1.29e-03	ASV_783	Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_p-1088-a5_gut_group
111	1.29e-03	ASV_8	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum
112	1.29e-03	ASV_819	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Flavonifractor
113	1.29e-03	ASV_83	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_9
114	1.29e-03	ASV_837	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Agathobacter
116	1.29e-03	ASV_90	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella
117	1.29e-03	ASV_902	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002
118	1.29e-03	ASV_91	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003
120	1.29e-03	ASV_953	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group
121	1.29e-03	ASV_963	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Anaerosporobacter
47	2.46e-03	ASV_2183	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_3
61	2.46e-03	ASV_2731	Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Fretibacterium
91	2.46e-03	ASV_520	Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus
115	2.46e-03	ASV_887	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK4A136_group
119	2.46e-03	ASV_921	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-010
75	3.62e-03	ASV_3698	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelatoclostridium
97	3.62e-03	ASV_601	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009
17	5.99e-03	ASV_1258	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-006
52	9.51e-03	ASV_2319	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Fusicatenibacter
64	1.64e-02	ASV_2981	Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae_Planococcus
26	1.85e-02	ASV_1509	Bacteria_Firmicutes_Bacilli_Lactobacillales_Lactobacillaceae_Lactobacillus
71	1.85e-02	ASV_3393	Bacteria_Firmicutes_Bacilli_Bacillales_Staphylococcaceae_Staphylococcus
92	2.52e-02	ASV_534	Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae_Devosia
41	2.94e-02	ASV_2068	Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium_1
46	2.94e-02	ASV_2134	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_2
51	3.12e-02	ASV_2306	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-001
45	3.65e-02	ASV_2120	Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_CPla-4_termite_group

These are genera that are differentailly abundant between sample types and their false discovery corrected p-value. ASVs are listed by significance (p < 0.05).

We will now plot out all these taxa in comparison to grab samples.

##             x       xmin       xmax
## 1 -1.11267855 -1.8019687 -0.4233884
## 2  0.01801409 -0.5188173  0.5548455
## 3 -0.88724045 -1.5615566 -0.2129243
## 4 -0.06100509 -0.5700795  0.4480693
## 5 -0.80587250 -1.4864173 -0.1253277
## 6 -4.40965054 -5.4032656 -3.4160355
##                                           taxa
## 1 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 2 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 3 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 4 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 5 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 6 Lachnospiraceae_Lachnospiraceae_ND3007_group
##                                     variable     Phylum
## 1             Feces\nDifferential\nAbundance Firmicutes
## 2      Stomach Tube\nDifferential\nAbundance Firmicutes
## 3   Liquid Strained\nDifferential\nAbundance Firmicutes
## 4             Solid\nDifferential\nAbundance Firmicutes
## 5 Liquid Unstrained\nDifferential\nAbundance Firmicutes
## 6             Feces\nDifferential\nAbundance Firmicutes

This is a graph of genera that are significantly differentially abundant across a sample type. The graph is of our model coefficent with a 95% confidence interval. Negative coefficients suggest that a taxon is differentially abundant across that sample type and that samples from that type are expected to have lower relative abundance. Conversely, postive coefficients suggest that a taxon is differentially abundant across that sample type and that samples from that type are expected to have higher relative abundance.

Let’s take a deeper dive into how these gnera separate by phyla.

## 
##     Actinobacteria      Bacteroidetes        Chloroflexi 
##                  7                 12                  1 
##      Elusimicrobia Epsilonbacteraeota      Euryarchaeota 
##                  2                  1                  3 
##      Fibrobacteres         Firmicutes       Fusobacteria 
##                  1                 80                  1 
##     Planctomycetes     Proteobacteria       Spirochaetes 
##                  2                  7                  1 
##      Synergistetes        Tenericutes    Verrucomicrobia 
##                  1                  1                  1

80 of the 121 significantly different taxa are Firmicutes. If we move the p-value to > 0.01 there are 75 significantly different taxa which are Firmicutes. We will graph out just these 80 taxa.

A majority of these genera in the phylum Firmicutes are in the families Ruminococcaceae and Lachnospiraceae.

This is the graph of the genera that are significantly differentially abundant in the phylum Bacteroidetes.

We can look more closely at one of these ASVs (ASV_622) that feces has a strong negative impact on.

##                                                                     ASV_622 
## "Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium"

## OTU Table:          [1 taxa and 68 samples]
##                      taxa are rows
##         282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_622  31  32  15  17  19  14  10   8  18  10  10  24  13  14  17  23
##         298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_622  35  14  18  17  15  20  26  34   4  23  25  30  35  19  15  18
##         360 361 362 363 365 366 367 368 369 370 371 372 373 374 375 376
## ASV_622  36  39  10   2  14   0   0   0   0   0   0   0   0   1   0   0
##         378 379 380 381 382 383 384 385 386 387 388 389 390 505 506 507
## ASV_622   0  31  29  37  46  16  35  18  34  48  22  43   6   8   7  11
##         508 509 510 511
## ASV_622   6  54  28  34

This is the feature table for ASV_622, it looks as those there is only one read for Lachnospiraceae Oribacterium in feces.

## 
## Call:
## bbdml(formula = ASV_622 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = ps_gen)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.57156    0.12016 -46.367
## Sample_TypeFeces             -5.55295    1.01064  -5.494
## Sample_TypeStomach Tube      -0.27180    0.12128  -2.241
## Sample_TypeLiquid Strained   -0.14208    0.11770  -1.207
## Sample_TypeLiquid Unstrained -0.27676    0.13396  -2.066
## Sample_TypeSolid             -0.03301    0.10920  -0.302
## CowIDCow_2477                 0.21587    0.10444   2.067
## CowIDCow_2549                 0.17021    0.10772   1.580
## CowIDCow_796                 -0.17494    0.11833  -1.478
## DayDay_7                     -0.06593    0.09719  -0.678
## DayDay_9                      0.04943    0.09005   0.549
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces                      0.000000994 ***
## Sample_TypeStomach Tube                    0.0290 *  
## Sample_TypeLiquid Strained                 0.2324    
## Sample_TypeLiquid Unstrained               0.0435 *  
## Sample_TypeSolid                           0.7636    
## CowIDCow_2477                              0.0434 *  
## CowIDCow_2549                              0.1197    
## CowIDCow_796                               0.1449    
## DayDay_7                                   0.5003    
## DayDay_9                                   0.5852    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -9.0948     0.4929  -18.45 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -181.86

Here we see the output of our hypothesis test. Feces is significantly different that other rumen samples. Additionally, both liquid straind and stomach tube samples have significantly lower abundance of this taxa when compared to grab samples. There is individual cow variation, but the day doesn’t make a significant difference.

Let’s graph out the abundance of Lachnospiraceae Oribacterium.

These graphs show that ASV_622 Lachnospiraceae Oribacterium is in lower abundance in fecal samples.

## 
## Call:
## bbdml(formula = ASV_20 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -1.69605    0.09946 -17.052
## Sample_TypeFeces             -0.43825    0.11515  -3.806
## Sample_TypeStomach Tube       0.20191    0.10317   1.957
## Sample_TypeLiquid Strained    1.33969    0.09448  14.180
## Sample_TypeLiquid Unstrained  0.77679    0.10850   7.159
## Sample_TypeSolid              0.03152    0.10552   0.299
## CowIDCow_2477                 0.12762    0.08214   1.554
## CowIDCow_2549                 0.11890    0.08238   1.443
## CowIDCow_796                  0.01186    0.08332   0.142
## DayDay_7                      0.00962    0.07586   0.127
## DayDay_9                      0.08982    0.06897   1.302
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces                         0.000352 ***
## Sample_TypeStomach Tube                  0.055336 .  
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained        0.00000000189 ***
## Sample_TypeSolid                         0.766242    
## CowIDCow_2477                            0.125893    
## CowIDCow_2549                            0.154474    
## CowIDCow_796                             0.887356    
## DayDay_7                                 0.899541    
## DayDay_9                                 0.198148    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -4.6695     0.1762   -26.5 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -434.14

## 
## Call:
## bbdml(formula = ASV_20 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams2)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -1.69605    0.09946 -17.052
## Sample_TypeFeces             -0.43825    0.11515  -3.806
## Sample_TypeStomach Tube       0.20191    0.10317   1.957
## Sample_TypeLiquid Strained    1.33969    0.09448  14.180
## Sample_TypeLiquid Unstrained  0.77679    0.10850   7.159
## Sample_TypeSolid              0.03152    0.10552   0.299
## CowIDCow_2477                 0.12762    0.08214   1.554
## CowIDCow_2549                 0.11890    0.08238   1.443
## CowIDCow_796                  0.01186    0.08332   0.142
## DayDay_7                      0.00962    0.07586   0.127
## DayDay_9                      0.08982    0.06897   1.302
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces                         0.000352 ***
## Sample_TypeStomach Tube                  0.055336 .  
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained        0.00000000189 ***
## Sample_TypeSolid                         0.766242    
## CowIDCow_2477                            0.125893    
## CowIDCow_2549                            0.154474    
## CowIDCow_796                             0.887356    
## DayDay_7                                 0.899541    
## DayDay_9                                 0.198148    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -4.6695     0.1762   -26.5 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -434.14

Hypothesis testing of relative abundance of Prevotellaceae.

## 
## Call:
## bbdml(formula = ASV_3 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -0.65855    0.04447 -14.809
## Sample_TypeFeces              1.76038    0.04717  37.323
## Sample_TypeStomach Tube       0.03498    0.04563   0.767
## Sample_TypeLiquid Strained   -0.22649    0.04665  -4.855
## Sample_TypeLiquid Unstrained  0.07624    0.05140   1.483
## Sample_TypeSolid              0.13751    0.04495   3.059
## CowIDCow_2477                 0.03856    0.03821   1.009
## CowIDCow_2549                -0.09324    0.03885  -2.400
## CowIDCow_796                  0.03687    0.03858   0.956
## DayDay_7                     -0.03020    0.03485  -0.867
## DayDay_9                     -0.04726    0.03254  -1.452
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.4465    
## Sample_TypeLiquid Strained                0.00001 ***
## Sample_TypeLiquid Unstrained               0.1436    
## Sample_TypeSolid                           0.0034 ** 
## CowIDCow_2477                              0.3172    
## CowIDCow_2549                              0.0197 *  
## CowIDCow_796                               0.3433    
## DayDay_7                                   0.3899    
## DayDay_9                                   0.1520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0056     0.1917  -31.33 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -402.99

## 
## Call:
## bbdml(formula = ASV_3 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams2)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -0.65855    0.04447 -14.809
## Sample_TypeFeces              1.76038    0.04717  37.323
## Sample_TypeStomach Tube       0.03498    0.04563   0.767
## Sample_TypeLiquid Strained   -0.22649    0.04665  -4.855
## Sample_TypeLiquid Unstrained  0.07624    0.05140   1.483
## Sample_TypeSolid              0.13751    0.04495   3.059
## CowIDCow_2477                 0.03856    0.03821   1.009
## CowIDCow_2549                -0.09324    0.03885  -2.400
## CowIDCow_796                  0.03687    0.03858   0.956
## DayDay_7                     -0.03020    0.03485  -0.867
## DayDay_9                     -0.04726    0.03254  -1.452
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.4465    
## Sample_TypeLiquid Strained                0.00001 ***
## Sample_TypeLiquid Unstrained               0.1436    
## Sample_TypeSolid                           0.0034 ** 
## CowIDCow_2477                              0.3172    
## CowIDCow_2549                              0.0197 *  
## CowIDCow_796                               0.3433    
## DayDay_7                                   0.3899    
## DayDay_9                                   0.1520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0056     0.1917  -31.33 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -402.99

Hypothesis testing of relative abundance of Ruminococcaceae.

## 
## Call:
## bbdml(formula = ASV_2 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                   0.042374   0.064372   0.658
## Sample_TypeFeces             -1.810536   0.079047 -22.905
## Sample_TypeStomach Tube      -0.174821   0.064394  -2.715
## Sample_TypeLiquid Strained   -0.947437   0.068013 -13.930
## Sample_TypeLiquid Unstrained -0.649631   0.075585  -8.595
## Sample_TypeSolid             -0.139437   0.064160  -2.173
## CowIDCow_2477                -0.131409   0.057870  -2.271
## CowIDCow_2549                 0.004171   0.057745   0.072
## CowIDCow_796                 -0.040359   0.057518  -0.702
## DayDay_7                      0.014258   0.052239   0.273
## DayDay_9                     -0.029545   0.048922  -0.604
##                                          Pr(>|t|)    
## (Intercept)                                0.5131    
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.0088 ** 
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained      0.0000000000082 ***
## Sample_TypeSolid                           0.0340 *  
## CowIDCow_2477                              0.0270 *  
## CowIDCow_2549                              0.9427    
## CowIDCow_796                               0.4858    
## DayDay_7                                   0.7859    
## DayDay_9                                   0.5483    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -5.1338     0.1794  -28.62 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -429.01

## 
## Call:
## bbdml(formula = ASV_2 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams2)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                   0.042374   0.064372   0.658
## Sample_TypeFeces             -1.810536   0.079047 -22.905
## Sample_TypeStomach Tube      -0.174821   0.064394  -2.715
## Sample_TypeLiquid Strained   -0.947437   0.068013 -13.930
## Sample_TypeLiquid Unstrained -0.649631   0.075585  -8.595
## Sample_TypeSolid             -0.139437   0.064160  -2.173
## CowIDCow_2477                -0.131409   0.057870  -2.271
## CowIDCow_2549                 0.004171   0.057745   0.072
## CowIDCow_796                 -0.040359   0.057518  -0.702
## DayDay_7                      0.014258   0.052239   0.273
## DayDay_9                     -0.029545   0.048922  -0.604
##                                          Pr(>|t|)    
## (Intercept)                                0.5131    
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.0088 ** 
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained      0.0000000000082 ***
## Sample_TypeSolid                           0.0340 *  
## CowIDCow_2477                              0.0270 *  
## CowIDCow_2549                              0.9427    
## CowIDCow_796                               0.4858    
## DayDay_7                                   0.7859    
## DayDay_9                                   0.5483    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -5.1338     0.1794  -28.62 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -429.01

Hypothesis testing of relative abundance of Lachnospiraceae.

Alpha Diversity

Richness

Richness is defined as an estimate the number of ASVs in a sample. Next we will use breakaway to estimate the number of missing species based on the sequence depth and number of rare taxa in the data. These estimates account for different sequencing depths!

The error bars here are quite large, but this is to be expected as there is a lot of uncertainty in estimating alpha diversity.

Next we will test the hypothesis that different sample types have the same microbial diversity.

##                               Estimates Standard Errors p-values
## (Intercept)                  2021.81504        48.63103    0.000
## Sample_TypeGrab Sample       2097.41821       169.47911    0.000
## Sample_TypeLiquid Strained   2252.37940       185.14713    0.000
## Sample_TypeLiquid Unstrained 2267.87495       160.57081    0.000
## Sample_TypeStomach Tube      1590.78095       118.21733    0.000
## Sample_TypeSolid             1810.28830       123.71986    0.000
## CowIDCow_2477                  78.63928        84.39906    0.351
## CowIDCow_2549                 156.77270        99.34590    0.115
## CowIDCow_796                  -57.60818       106.37136    0.588
## DayDay_7                      -36.47393        88.72531    0.681
## DayDay_9                     -112.34992        77.42422    0.147

##                               Estimates Standard Errors p-values
## Sample_TypeFeces             2021.75358        73.87303    0.000
## Sample_TypeGrab Sample       4119.10429       169.47362    0.000
## Sample_TypeLiquid Strained   4274.33138       185.14037    0.000
## Sample_TypeLiquid Unstrained 4289.55899       160.56363    0.000
## Sample_TypeStomach Tube      3612.48064       118.20446    0.000
## Sample_TypeSolid             3832.13025       123.70992    0.000
## CowIDCow_2477                  78.70047        84.38617    0.351
## CowIDCow_2549                 156.85072        99.33510    0.114
## CowIDCow_796                  -57.62115       106.36304    0.588
## DayDay_7                      -36.52707        88.71495    0.681
## DayDay_9                     -112.31280        77.41588    0.147

##                                Estimates Standard Errors p-values
## (Intercept)                   4119.16582        48.63357    0.000
## Sample_TypeFeces             -2097.31618        73.89187    0.000
## Sample_TypeLiquid Strained     155.03662       185.15015    0.402
## Sample_TypeLiquid Unstrained   170.61198       160.57402    0.288
## Sample_TypeStomach Tube       -506.48308       118.22309    0.000
## Sample_TypeSolid              -286.99295       123.72430    0.020
## CowIDCow_2477                   78.61278        84.40483    0.352
## CowIDCow_2549                  156.79239        99.35073    0.115
## CowIDCow_796                   -57.70879       106.37509    0.587
## DayDay_7                       -36.47887        88.72994    0.681
## DayDay_9                      -112.31633        77.42795    0.147

When you break the rumen samples up into different sample types betta() estimates the mean species-level diversity are significantly different compared to fecal samples. Neither the cow or day caused a significant shift in species level diversity. When compared to the grab sample the stomach tube and solid samples have significatly less mean species-level diversity.

Evenness

Evenness is defined as how balanced the ASVs are; in other words do they exist in approximately the same relative abundance (1=very even). DivNet will estimate Shannon diversity in the presence of an ecological/microbial network! It also adjusts for different sequencing depths.

Here we will first look to see if samples types differ.

First, we will graph divnet’s estimation of shannon diversity.

Let’s look at hypothesis testing for DivNet estimates of shannon and diversity.

## [1] "hypothesis test for Shannon diversity"

## Hypothesis testing:
##   p-value for global test: 0

##                                Estimates Standard Errors p-values
## (Intercept)                   6.28626928     0.007833397    0.000
## Sample_TypeGrab Sample        0.42233374     0.019789481    0.000
## Sample_TypeLiquid Strained    0.33332816     0.016776556    0.000
## Sample_TypeLiquid Unstrained  0.45963678     0.024974179    0.000
## Sample_TypeSolid              0.40306231     0.014932992    0.000
## Sample_TypeStomach Tube       0.35163894     0.019836911    0.000
## CowIDCow_2477                -0.07519473     0.014980824    0.000
## CowIDCow_2549                -0.03249017     0.015576432    0.037
## CowIDCow_796                 -0.06513514     0.018650721    0.000
## DayDay_7                     -0.01866298     0.013726526    0.174
## DayDay_9                      0.04294924     0.014576081    0.003

## Hypothesis testing:
##   p-value for global test: 0

##                                 Estimates Standard Errors p-values
## (Intercept)                   6.736599905     0.007388884    0.000
## Sample_TypeFeces             -0.409523052     0.041617576    0.000
## Sample_TypeStomach Tube      -0.095140434     0.013441522    0.000
## Sample_TypeLiquid Strained   -0.090070120     0.017307448    0.000
## Sample_TypeSolid             -0.023506296     0.019564916    0.230
## Sample_TypeLiquid Unstrained  0.021480919     0.015079179    0.154
## CowIDCow_2477                -0.095425089     0.017819806    0.000
## CowIDCow_2549                -0.044188813     0.014767877    0.003
## CowIDCow_796                 -0.087036353     0.016435309    0.000
## DayDay_7                     -0.039248141     0.014234720    0.006
## DayDay_9                      0.007514973     0.012613441    0.551

Both the cow and day had a significant effect on evenness. Fecal samples had significantly lower evenness than samples from the rumen.

We will put a graph of the richness and evenness together as a figure for publication

Beta Diversity

We will plot the bray-curtis distances from Divnet. DivNet uses covariate information to share strength across samples and obtain an estimate about the beta diversity of the ecosystem not the samples.

Graph of estimates of bray-curtis distance from model with day and cowID

Graph of estimates of bray-curtis distance from model without day and cowID.

Grab vs fecal samples

We will remove other a few sample types to compress the data down and look just at the grab sample and feces.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5164 taxa and 24 samples ]
## sample_data() Sample Data:       [ 24 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5164 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5164 tips and 5162 internal nodes ]

After subsetting the data we have 5164 ASVs in 24 samples.

Since we saw in the DPCoA that there were two populations of Firmicutes and Bacteriodests that separated rumen and fecal samples, we can ingestigate whether these are different genera or different species that make up this differences.

## [1] "Found in feces not in GS"

## [1] "Barnesiellaceae"       "Chitinophagaceae"      "p-2534-18B5_gut_group"
## [4] "GZKB124"               "Hymenobacteraceae"

## [1] "Found in GS not in feces"

##  [1] "Leuconostocaceae"       "Carnobacteriaceae"     
##  [3] "Aerococcaceae"          "Syntrophomonadaceae"   
##  [5] "Bacteroidetes_BD2-2"    "PeH15"                 
##  [7] "M2PB4-65_termite_group" "COB_P4-1_termite_group"
##  [9] "Spirosomaceae"          "Porphyromonadaceae"

These are the families that are found in one and not the other sample type.

## [1] "Found in feces not in GS"

##  [1] "Hungatella"                   "Coprococcus_3"               
##  [3] "Lachnospiraceae_NC2004_group" "Cellulosilyticum"            
##  [5] "Terrisporobacter"             "Clostridioides"              
##  [7] "Paeniclostridium"             "Ruminococcaceae_UCG-011"     
##  [9] "Breznakia"                    "Allobaculum"                 
## [11] "Dielma"                       "Jeotgalicoccus"              
## [13] "Lysinibacillus"               "Odoribacter"                 
## [15] "Sanguibacteroides"            "Taibaiella"                  
## [17] "Hymenobacter"                 "Harryflintia"                
## [19] "Negativibacillus"             "Fournierella"                
## [21] "Anaerofilum"                  "Pygmaiobacter"               
## [23] "Faecalibacterium"             "Intestinimonas"              
## [25] "Lachnoclostridium_5"

## [1] "Found in GS not in feces"

##  [1] "Acetatifactor"                "Lachnospiraceae_UCG-006"     
##  [3] "Shuttleworthia"               "Lachnoclostridium_1"         
##  [5] "Lachnoclostridium_12"         "Lachnospira"                 
##  [7] "Lachnospiraceae_NK4B4_group"  "GCA-900066575"               
##  [9] "Veillonellaceae_UCG-001"      "Quinella"                    
## [11] "Schwartzia"                   "Selenomonas_4"               
## [13] "Helcococcus"                  "Peptoniphilus"               
## [15] "Erysipelotrichaceae_UCG-008"  "Weissella"                   
## [17] "Desemzia"                     "Aerococcus"                  
## [19] "Pelospora"                    "Prevotellaceae_YAB2003_group"
## [21] "U29-B03"                      "Rikenella"                   
## [23] "Dyadobacter"                  "Tannerella"                  
## [25] "Porphyromonas"                "Angelakisella"               
## [27] "Ruminococcaceae_UCG-001"      "CAG-352"                     
## [29] "Ruminococcaceae_UCG-012"

These are the genera that are found in one and not the other sample type.

## [1] "Found in feces not in GS"

## [1] "sedimentorum" "ramosum"      "massiliensis"

## [1] "Found in GS not in feces"

##  [1] "intestinalis"  "xylanivorans"  "fibrisolvens"  "hungatei"     
##  [5] "succinivorans" "lipolyticus"   "ovis"          "indolicus"    
##  [9] "equigenerosi"  "incerta"       "ruminis"       "bryantii"     
## [13] "hamtensis"     "levii"

These are the species that are found in one and not the other sample type.

There are 1134 ASVs that are in feces, which are not in grab samples and there are 2102 ASVs in grab samples that are not in feces.

Corncob

We test all the taxa in our data to see if they are differentially-abundant or differentially-variable. The differentialTest function will these tests on all taxa, while controlling the false discovery rate to account for multiple comparisons.

Although there are species to species differences between samples we might expect this to be the normal variation in sample collection. Thus, we are most concerned with particular family or generna that might be excluded when sampling via different methods.

As we saw that when we graphed out relative abundance of families we will check to see if these differences are significant after taking into account library size differences. Then we will look lower taxonomically.

##                                            ASV_2 
##                     "Firmicutes_Lachnospiraceae" 
##                                          ASV_348 
##                   "Firmicutes_Defluviitaleaceae" 
##                                           ASV_23 
##                     "Firmicutes_Veillonellaceae" 
##                                           ASV_48 
##               "Firmicutes_Peptostreptococcaceae" 
##                                         ASV_1956 
##       "Firmicutes_Clostridiales_vadinBB60_group" 
##                                          ASV_246 
##                 "Tenericutes_Anaeroplasmataceae" 
##                                          ASV_117 
##                    "Firmicutes_Streptococcaceae" 
##                                         ASV_2071 
##                      "Firmicutes_Planococcaceae" 
##                                          ASV_384 
##                      "Firmicutes_Peptococcaceae" 
##                                         ASV_1682 
##                    "Firmicutes_Clostridiaceae_1" 
##                                          ASV_442 
##                  "Firmicutes_Acidaminococcaceae" 
##                                         ASV_1016 
##                      "Firmicutes_Eubacteriaceae" 
##                                          ASV_330 
##                "Verrucomicrobia_Akkermansiaceae" 
##                                         ASV_2079 
##          "Epsilonbacteraeota_Campylobacteraceae" 
##                                         ASV_1100 
##                "Elusimicrobia_Elusimicrobiaceae" 
##                                          ASV_783 
##                   "Planctomycetes_Pirellulaceae" 
##                                          ASV_563 
##                 "Elusimicrobia_Endomicrobiaceae" 
##                                          ASV_171 
##             "Proteobacteria_Succinivibrionaceae" 
##                                         ASV_1336 
##                "Proteobacteria_Burkholderiaceae" 
##                                         ASV_2314 
##                  "Proteobacteria_Oligoflexaceae" 
##                                            ASV_7 
##              "Euryarchaeota_Methanobacteriaceae" 
##                                          ASV_231 
##          "Euryarchaeota_Methanomethylophilaceae" 
##                                         ASV_1434 
##            "Euryarchaeota_Methanocorpusculaceae" 
##                                          ASV_534 
##                     "Proteobacteria_Devosiaceae" 
##                                           ASV_29 
##                   "Spirochaetes_Spirochaetaceae" 
##                                         ASV_1548 
##                   "Lentisphaerae_Victivallaceae" 
##                                         ASV_2068 
##              "Actinobacteria_Corynebacteriaceae" 
##                                          ASV_656 
## "Actinobacteria_Coriobacteriales_Incertae_Sedis" 
##                                          ASV_172 
##                 "Actinobacteria_Eggerthellaceae" 
##                                           ASV_90 
##                    "Actinobacteria_Atopobiaceae" 
##                                           ASV_68 
##                 "Fibrobacteres_Fibrobacteraceae" 
##                                          ASV_409 
##                    "Chloroflexi_Anaerolineaceae" 
##                                          ASV_499 
##                   "Synergistetes_Synergistaceae" 
##                                            ASV_1 
##                 "Firmicutes_Christensenellaceae" 
##                                           ASV_26 
##                   "Bacteroidetes_Prevotellaceae" 
##                                           ASV_36 
##                   "Bacteroidetes_Bacteroidaceae" 
##                                         ASV_2770 
##                   "Bacteroidetes_Marinifilaceae" 
##                                          ASV_995 
##                   "Bacteroidetes_Muribaculaceae" 
##                                         ASV_1084 
##                             "Bacteroidetes_F082" 
##                                          ASV_994 
##              "Bacteroidetes_Sphingobacteriaceae" 
##                                          ASV_197 
##     "Bacteroidetes_Bacteroidales_BS11_gut_group" 
##                                           ASV_60 
##                    "Bacteroidetes_Rikenellaceae" 
##                                          ASV_572 
##                "Bacteroidetes_Marinilabiliaceae" 
##                                          ASV_536 
##                         "Bacteroidetes_p-251-o5" 
##                                         ASV_2217 
##                   "Bacteroidetes_Tannerellaceae" 
##                                          ASV_822 
##                "Bacteroidetes_Paludibacteraceae" 
##                                          ASV_651 
##         "Bacteroidetes_Bacteroidales_RF16_group" 
##                                            ASV_3 
##                     "Firmicutes_Ruminococcaceae"

There are 48 families that are significantly different between fecal and grab samples.

These are the families that are significantly lower and higher in abundance.

## 
## -1  1 
## 30 18

There are 18 families significantly increased and 30 significantly decreased in relative abundance compared to grab samples.


	x	taxa	Family
3	-5.5479763	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae (ASV_23)	Veillonellaceae
41	-4.8958710	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidales_BS11_gut_group (ASV_197)	Bacteroidales_BS11_gut_group
43	-4.8435765	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Marinilabiliaceae (ASV_572)	Marinilabiliaceae
17	-4.4552940	Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae (ASV_563)	Endomicrobiaceae
31	-4.4179317	Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae (ASV_68)	Fibrobacteraceae
33	-4.4073698	Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae (ASV_499)	Synergistaceae
18	-3.8406088	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae (ASV_171)	Succinivibrionaceae
22	-3.8244025	Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae (ASV_231)	Methanomethylophilaceae
6	-3.0967818	Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae (ASV_246)	Anaeroplasmataceae
32	-2.9542980	Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae (ASV_409)	Anaerolineaceae
24	-2.9465011	Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae (ASV_534)	Devosiaceae
20	-2.3601932	Bacteria_Proteobacteria_Deltaproteobacteria_Oligoflexales_Oligoflexaceae (ASV_2314)	Oligoflexaceae
44	-2.1251118	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_p-251-o5 (ASV_536)	p-251-o5
28	-1.9605047	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis (ASV_656)	Coriobacteriales_Incertae_Sedis
30	-1.8100719	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae (ASV_90)	Atopobiaceae
40	-1.6584080	Bacteria_Bacteroidetes_Bacteroidia_Sphingobacteriales_Sphingobacteriaceae (ASV_994)	Sphingobacteriaceae
39	-1.5196692	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_F082 (ASV_1084)	F082
25	-1.5130522	Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae (ASV_29)	Spirochaetaceae
21	-1.4923050	Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae (ASV_7)	Methanobacteriaceae
1	-1.4413798	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae (ASV_2)	Lachnospiraceae
27	-1.3854374	Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae (ASV_2068)	Corynebacteriaceae
12	-1.1462353	Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae (ASV_1016)	Eubacteriaceae
7	-1.1093855	Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae (ASV_117)	Streptococcaceae
34	-1.0002190	Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae (ASV_1)	Christensenellaceae
2	-0.9622930	Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae (ASV_348)	Defluviitaleaceae
29	-0.9606860	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae (ASV_172)	Eggerthellaceae
19	-0.8850722	Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae (ASV_1336)	Burkholderiaceae
11	-0.6191481	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae (ASV_442)	Acidaminococcaceae
38	-0.4438094	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Muribaculaceae (ASV_995)	Muribaculaceae
35	-0.3491789	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae (ASV_26)	Prevotellaceae
16	0.7348044	Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae (ASV_783)	Pirellulaceae
42	0.8358951	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae (ASV_60)	Rikenellaceae
37	0.9817063	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Marinifilaceae (ASV_2770)	Marinifilaceae
9	1.0539220	Bacteria_Firmicutes_Clostridia_Clostridiales_Peptococcaceae (ASV_384)	Peptococcaceae
47	1.1177019	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidales_RF16_group (ASV_651)	Bacteroidales_RF16_group
48	1.1785720	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae (ASV_3)	Ruminococcaceae
15	1.3666778	Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae (ASV_1100)	Elusimicrobiaceae
10	1.6291444	Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1 (ASV_1682)	Clostridiaceae_1
45	1.7352336	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae (ASV_2217)	Tannerellaceae
5	2.2880851	Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_vadinBB60_group (ASV_1956)	Clostridiales_vadinBB60_group
14	2.6322533	Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae (ASV_2079)	Campylobacteraceae
26	3.0609734	Bacteria_Lentisphaerae_Lentisphaeria_Victivallales_Victivallaceae (ASV_1548)	Victivallaceae
46	3.2160642	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Paludibacteraceae (ASV_822)	Paludibacteraceae
8	3.3023998	Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae (ASV_2071)	Planococcaceae
23	3.9963476	Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae (ASV_1434)	Methanocorpusculaceae
4	4.5037536	Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae (ASV_48)	Peptostreptococcaceae
13	4.6224111	Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae (ASV_330)	Akkermansiaceae
36	5.3588153	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae (ASV_36)	Bacteroidaceae

## [1] "Model for Peptostreptococcaceae"

## 
## Call:
## bbdml(formula = ASV_48 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value          Pr(>|t|)    
## (Intercept)       -6.9644     0.3372 -20.655 0.000000000000582 ***
## Sample_TypeFeces   4.3477     0.3223  13.491 0.000000000370577 ***
## CowIDCow_2477     -0.2735     0.1186  -2.305            0.0349 *  
## CowIDCow_2549     -0.1772     0.1215  -1.458            0.1641    
## CowIDCow_796       0.2097     0.1063   1.972            0.0661 .  
## DayDay_7           0.2602     0.1047   2.485            0.0244 *  
## DayDay_9           0.4111     0.1024   4.015            0.0010 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value        Pr(>|t|)    
## (Intercept)  -6.7448     0.4179  -16.14 0.0000000000254 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -83.154

## [1] "Model for Akkermansiaceae"

## 
## Call:
## bbdml(formula = ASV_330 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)      -8.27005    0.64229 -12.876 0.000000000737 ***
## Sample_TypeFeces  4.71006    0.61628   7.643 0.000000997988 ***
## CowIDCow_2477     0.30451    0.23539   1.294         0.2142    
## CowIDCow_2549     0.59090    0.23030   2.566         0.0207 *  
## CowIDCow_796      0.51348    0.22589   2.273         0.0372 *  
## DayDay_7          0.04634    0.18572   0.250         0.8061    
## DayDay_9         -0.08257    0.19196  -0.430         0.6728    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)   -6.061      0.451  -13.44 0.000000000392 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -68.472

## [1] "Model for Bacteroidaceae"

## 
## Call:
## bbdml(formula = ASV_36 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value          Pr(>|t|)    
## (Intercept)      -6.58850    0.27165 -24.254 0.000000000000048 ***
## Sample_TypeFeces  5.48235    0.26807  20.452 0.000000000000678 ***
## CowIDCow_2477    -0.22519    0.05542  -4.064          0.000903 ***
## CowIDCow_2549    -0.08155    0.05860  -1.392          0.183085    
## CowIDCow_796     -0.24183    0.05468  -4.423          0.000427 ***
## DayDay_7         -0.13691    0.04904  -2.792          0.013058 *  
## DayDay_9         -0.11920    0.04946  -2.410          0.028333 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)  -7.6553     0.5714   -13.4 0.000000000411 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -82.185

## [1] "Model for Veillonellaceae"

## 
## Call:
## bbdml(formula = ASV_23 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value             Pr(>|t|)    
## (Intercept)      -3.75237    0.11655 -32.195 0.000000000000000564 ***
## Sample_TypeFeces -5.62348    0.57920  -9.709 0.000000041362350627 ***
## CowIDCow_2477     0.33876    0.13059   2.594              0.01958 *  
## CowIDCow_2549     0.20408    0.13773   1.482              0.15782    
## CowIDCow_796      0.08529    0.13895   0.614              0.54797    
## DayDay_7         -0.38034    0.10482  -3.629              0.00226 ** 
## DayDay_9         -0.27460    0.11020  -2.492              0.02406 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02     102.87  -0.175    0.863
## 
## 
## Log-likelihood: -45.747

## [1] "Model for Marinifilaceae"

## 
## Call:
## bbdml(formula = ASV_2770 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value          Pr(>|t|)    
## (Intercept)       -6.9769     0.3349 -20.834 0.000000000000509 ***
## Sample_TypeFeces   0.9070     0.2727   3.327           0.00427 ** 
## CowIDCow_2477     -0.7115     0.3571  -1.992           0.06369 .  
## CowIDCow_2549     -0.2403     0.3590  -0.669           0.51287    
## CowIDCow_796       0.4016     0.2624   1.531           0.14539    
## DayDay_7          -0.2217     0.2529  -0.877           0.39365    
## DayDay_9          -0.3895     0.2695  -1.445           0.16769    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02     116.78  -0.154    0.879
## 
## 
## Log-likelihood: -43.09

## [1] "Model for Bacteroidales_BS11_gut_group"

## 
## Call:
## bbdml(formula = ASV_197 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value           Pr(>|t|)    
## (Intercept)      -3.85845    0.15016 -25.696 0.0000000000000195 ***
## Sample_TypeFeces -4.77223    0.54227  -8.801 0.0000001575346194 ***
## CowIDCow_2477    -0.03706    0.16834  -0.220             0.8285    
## CowIDCow_2549    -0.34477    0.18772  -1.837             0.0849 .  
## CowIDCow_796     -0.02837    0.16832  -0.169             0.8682    
## DayDay_7         -0.26834    0.15820  -1.696             0.1092    
## DayDay_9          0.23722    0.14364   1.651             0.1181    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value     Pr(>|t|)    
## (Intercept)  -8.0549     0.8796  -9.157 0.0000000921 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -52.524

## [1] "Model for Fibrobacteraceae"

## 
## Call:
## bbdml(formula = ASV_29 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                   Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)      -2.647050   0.419377  -6.312 0.0000103 ***
## Sample_TypeFeces -1.669545   0.361365  -4.620  0.000284 ***
## CowIDCow_2477     0.003809   0.437963   0.009  0.993168    
## CowIDCow_2549     0.932873   0.414670   2.250  0.038898 *  
## CowIDCow_796     -0.121804   0.441738  -0.276  0.786278    
## DayDay_7          0.712349   0.360838   1.974  0.065887 .  
## DayDay_9         -0.148602   0.383329  -0.388  0.703375    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value    Pr(>|t|)    
## (Intercept)  -3.2789     0.3615  -9.071 0.000000105 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -134.17

## [1] "Model for Spirochaetaceae"

## 
## Call:
## bbdml(formula = ASV_68 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value           Pr(>|t|)    
## (Intercept)      -2.79001    0.11492 -24.279 0.0000000000000473 ***
## Sample_TypeFeces -4.49686    0.35791 -12.564 0.0000000010544203 ***
## CowIDCow_2477     0.31230    0.13279   2.352             0.0318 *  
## CowIDCow_2549     0.07762    0.14036   0.553             0.5879    
## CowIDCow_796      0.32862    0.13328   2.466             0.0254 *  
## DayDay_7         -0.05507    0.11132  -0.495             0.6275    
## DayDay_9         -0.01997    0.11247  -0.178             0.8613    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)  -6.8347     0.4993  -13.69 0.000000000299 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -78.079

## [1] "Model for Christensenellaceae"

## 
## Call:
## bbdml(formula = ASV_1 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value      Pr(>|t|)    
## (Intercept)       0.32931    0.16785   1.962        0.0674 .  
## Sample_TypeFeces -1.49195    0.13292 -11.224 0.00000000538 ***
## CowIDCow_2477     0.07971    0.18096   0.440        0.6655    
## CowIDCow_2549    -0.32060    0.18676  -1.717        0.1053    
## CowIDCow_796     -0.01653    0.17810  -0.093        0.9272    
## DayDay_7         -0.23819    0.15907  -1.497        0.1538    
## DayDay_9          0.02002    0.15683   0.128        0.9000    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)  -3.8665     0.2923  -13.23 0.000000000495 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -155.04

## [1] "Model for Rikenellaceae"

## 
## Call:
## bbdml(formula = ASV_60 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)      -1.15572    0.09990 -11.568 0.000000003491 ***
## Sample_TypeFeces  1.00619    0.07487  13.439 0.000000000392 ***
## CowIDCow_2477    -0.02057    0.10380  -0.198         0.8454    
## CowIDCow_2549    -0.19311    0.10515  -1.837         0.0849 .  
## CowIDCow_796      0.01051    0.10297   0.102         0.9200    
## DayDay_7         -0.07651    0.08972  -0.853         0.4064    
## DayDay_9         -0.01074    0.09039  -0.119         0.9069    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value        Pr(>|t|)    
## (Intercept)  -5.0415     0.3071  -16.41 0.0000000000197 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -141.9

We will look at a couple genera.

## [1] "Model for Fibrobacter"

## 
## Call:
## bbdml(formula = ASV_68 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_gen)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value    Pr(>|t|)    
## (Intercept)      -0.02493    0.28801  -0.087      0.9321    
## Sample_TypeFeces -2.73012    0.33675  -8.107 0.000000466 ***
## CowIDCow_2477     0.49871    0.32837   1.519      0.1483    
## CowIDCow_2549    -0.59569    0.33729  -1.766      0.0964 .  
## CowIDCow_796      0.38756    0.32444   1.195      0.2497    
## DayDay_7         -0.35679    0.28192  -1.266      0.2238    
## DayDay_9          0.18459    0.28904   0.639      0.5321    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value   Pr(>|t|)    
## (Intercept)  -3.1612     0.3596   -8.79 0.00000016 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -77.336

## [1] "Model for Treponema_2"

## 
## Call:
## bbdml(formula = ASV_29 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_gen)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value    Pr(>|t|)    
## (Intercept)       0.02493    0.28801   0.087      0.9321    
## Sample_TypeFeces  2.73012    0.33675   8.107 0.000000466 ***
## CowIDCow_2477    -0.49871    0.32837  -1.519      0.1483    
## CowIDCow_2549     0.59569    0.33729   1.766      0.0964 .  
## CowIDCow_796     -0.38756    0.32444  -1.195      0.2497    
## DayDay_7          0.35679    0.28192   1.266      0.2238    
## DayDay_9         -0.18459    0.28904  -0.639      0.5321    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value   Pr(>|t|)    
## (Intercept)  -3.1612     0.3596   -8.79 0.00000016 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -77.336

These are graphs of the relative abundance of families significantly differently between fecal and grab samples. This is figure 6.

After running corncob 131 genera could not be fit with the model, but 130 were fit to the model and 114 were significanlty differentially abundant genera and 657significanlty differentially abundant ASVs.

We will look into taxa could not be fit to the model and see if we can determine why.

## [1] 131

## OTU Table:          [131 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_4633   0   0   0   0   0   0   0   0   0   0   0   0   2   0   0   2
## ASV_429    2   2   3   2   4   2  12  13   5   5   6   6   0   0   0   0
## ASV_5279   0   0   0   0   0   0   0   0   0   0   0   3   0   0   0   0
## ASV_669    3   7   2   6   7   8  12   8   3   6   4   2   0   0   0   0
## ASV_713    0   0   0   0   0   0   0   0   0   0   0   0  28  20  27  22
## ASV_4679   0   0   0   0   1   1   0   0   2   0   0   1   0   0   0   0
## ASV_878    6   5   4   0   0   3   0   0   0   4   6   2   0   0   0   0
## ASV_4288   0   2   0   1   1   0   1   2   0   0   0   1   0   0   0   0
## ASV_793   15   7   7  12  16  15  14  14   9  17  13  19   0   0   0   0
## ASV_4973   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2583   1   2   1   1   1   0   2   1   0   5   0   4   0   0   0   0
## ASV_5230   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1393   0   0   0   0   0   0   0   0   0   0   0   0   7  19  14   5
## ASV_2417   0   0   1   0   0   0   0   0   0   1   0   1   0   0   0   0
## ASV_456   10   0   4   7   3   7   5   7   6   2   1   3   0   0   0   0
## ASV_4284   1   1   0   3   4   3   4   1   4   4   1   1   0   0   0   0
## ASV_2244   1   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_5146   0   1   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_2322   0   0   0   0   0   0   0   0   0   0   0   0   1   2   0   1
## ASV_113    0   0   0   0   0   0   0   0   0   0   0   0  33  31  32  47
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0  11  33  10  30
## ASV_4383   0   0   0   1   2   1   0   0   0   0   1   0   0   0   0   0
## ASV_4854   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5567   0   0   0   1   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5418   0   0   0   0   0   0   0   0   0   0   0   0   1   0   1   1
## ASV_4130   0   0   0   0   0   1   2   1   4   1   1   1   0   0   0   0
## ASV_1759   1   1   4   0   0   0   3   3   2   1   0   0   0   0   0   0
## ASV_413    0   1   1   0   0   1   0   0   0   0   0   1   0   0   0   0
## ASV_1612   0   0   0   0   1   1   0   0   0   0   0   1   0   0   0   1
## ASV_4673   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_3469   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3393   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2981   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4744   0   0   0   0   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_4508   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_3129   0   1   2   2   1   1   0   0   0   0   0   0   0   0   0   0
## ASV_5524   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_4013   0   0   0   0   1   0   0   2   1   2   0   0   0   0   0   0
## ASV_574    1   1   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_276    2   1   1   1   0   1   0   0   0   1   0   0   0   0   0   0
## ASV_511    3   4   3   1   1   0   5   7   4   2   2   3   0   0   0   0
## ASV_1518   1   0   2   0   0   2   0   2   0   2   2   0   0   0   0   0
## ASV_171   30  18  14   8   9  10   6  13   8   4   6   6   0   0   0   0
## ASV_1373   0   0   2   0   0   0   0   0   2   0   0   0   0   0   0   0
## ASV_1078   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1336   0   0   0   0   0   0   0   0   0   0   0   0   4   6   5   6
## ASV_5356   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   4
## ASV_2174   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2658   0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4109   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_1947   0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_503    0   1   1   1   0   0   0   0   1   1   0   0   0   0   0   0
## ASV_424    3   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_2419   0   0   1   2   1   1   0   0   0   0   0   0   0   0   0   0
## ASV_2915   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4015   1   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4126   0   0   0   0   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_3435   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2130   0   0   0   0   0   0   0   1   0   1   1   1   0   0   0   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4076   0   0   0   0   0   0   0   0   0   0   0   0   7   2   3   5
## ASV_5222   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_4211   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3936   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3276   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_221    1   0   2   0   1   1   2   2   0   0   0   0   0   0   0   0
## ASV_2401   0   1   0   0   1   0   0   0   0   0   0   0   0   0   1   0
## ASV_4992   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1856   0   0   0   0   0   1   0   0   1   0   0   0   0   0   0   1
## ASV_3262   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5025   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_2037   0   0   0   0   1   0   0   0   3   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_5555   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3123   1   0   0   0   0   1   0   0   0   0   0   0   0   0   1   1
## ASV_2044   0   1   2   0   1   0   0   0   0   1   0   1   0   0   0   0
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1389   2   1   0   3   4   6   3   5   4   1   1   1   0   0   0   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   1   4   1   1
## ASV_901    2   0   1   1   4   1   1   0   5   0   2   1   0   0   0   0
## ASV_578    2   4   6   6   5   0   3   4   4   2   2   3   0   0   0   0
## ASV_5600   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   2
## ASV_4378   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0  10   5  17   5
## ASV_3201   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_1042   0   1   0   0   0   0   0   0   0   0   1   1   0   0   0   1
## ASV_2594   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1307   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_2550   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1306   0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_3273   0   0   1   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_520    1   0   2   0   0   0   2   0   1   0   0   0   0   0   0   1
## ASV_3119   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_5589   0   1   0   0   1   0   1   0   0   1   0   0   0   0   0   0
## ASV_2687   0   0   0   0   0   0   0   0   0   0   0   0   2   6   2   2
## ASV_4612   0   0   0   1   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_5602   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_499    3   7   2   9   3   3   2   3   2   4   5   0   0   0   0   0
## ASV_2617   1   0   0   0   0   0   1   1   0   1   2   0   0   0   0   0
## ASV_2770   0   0   0   0   0   0   0   0   0   0   0   0   2   3   3   3
## ASV_5521   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_1658   3   4   1   2   0   3   3   1   0   3   2   3   0   0   0   0
## ASV_1213   1   1   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_994    0   0   1   0   2   0   0   1   0   0   0   0   0   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5568   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_2880   0   0   0   0   0   0   0   1   0   0   1   0   0   0   0   0
## ASV_3146   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_5036   0   0   0   0   0   0   1   0   0   2   0   0   0   0   0   0
## ASV_4270   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_4849   0   1   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2544   0   0   0   0   0   0   0   0   0   0   0   0   3   3   3   6
## ASV_1565   0   0   1   7   1   0   2   3   1   3   1   3   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   9   8   2   7
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   2   4   2   1
## ASV_4771   0   0   1   0   0   0   1   0   0   0   0   1   0   0   0   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2759   0   0   0   0   0   0   0   0   0   0   0   0   3   2   3   4
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   2
## ASV_5006   0   0   0   0   0   0   0   0   0   0   0   0   1   1   0   1
## ASV_2171   2   0   2   7   1   0   2   1   2   0   1   1   0   0   0   0
## ASV_3188   0   0   0   1   0   0   1   0   1   1   0   0   0   0   0   0
## ASV_2318   1   2   3   1   2   7   1   1   1   0   5   4   0   0   0   0
## ASV_4340   0   0   0   0   0   0   0   0   0   0   0   0   0   1   1   1
## ASV_5426   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_4633   3   1   6   1   1   0   0   0
## ASV_429    0   0   0   0   0   0   0   0
## ASV_5279   2   0   3   0   2   0   1   1
## ASV_669    0   0   0   0   0   0   0   0
## ASV_713   26  35  64  46  48  20  23  15
## ASV_4679   0   0   0   0   0   0   0   0
## ASV_878    0   0   0   0   0   0   0   0
## ASV_4288   0   0   0   0   0   0   0   0
## ASV_793    0   0   0   0   0   0   0   0
## ASV_4973   0   0   0   0   0   0   0   0
## ASV_2583   0   0   0   0   0   0   0   0
## ASV_5230   0   0   0   0   0   1   0   0
## ASV_1393   4  14  26   7   7   5   7   2
## ASV_2417   0   0   0   0   0   0   1   0
## ASV_456    0   0   0   0   0   0   0   0
## ASV_4284   0   0   0   0   0   0   0   0
## ASV_2244   0   0   0   0   0   0   0   0
## ASV_5146   0   0   0   0   0   0   0   0
## ASV_2322   4   3   4   4   6   8   2   7
## ASV_113   69  55 101  85  70  61  78  53
## ASV_147   35  31  74  84  52  64  93  54
## ASV_4383   1   0   0   0   0   0   0   0
## ASV_4854   0   0   0   0   0   0   0   0
## ASV_5567   0   0   0   0   0   0   0   0
## ASV_5123   1   0   2   1   1   1   0   3
## ASV_5340   0   0   1   0   0   0   0   0
## ASV_5418   1   2   0   0   0   1   0   0
## ASV_4130   0   0   0   0   0   0   0   0
## ASV_1759   0   0   0   0   0   0   0   0
## ASV_413    0   0   0   0   0   0   0   0
## ASV_1612   0   0   1   0   1   0   2   0
## ASV_4673   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   0   0   0
## ASV_3393   0   0   1   0   0   0   0   0
## ASV_5204   0   0   1   0   0   0   0   0
## ASV_2981   0   0   0   0   1   0   0   0
## ASV_4744   2   2   1   0   1   1   5   1
## ASV_4508   0   0   4   0   1   0   0   0
## ASV_3129   0   0   0   0   0   0   0   0
## ASV_5524   0   0   0   0   3   1   0   0
## ASV_4013   0   1   1   0   1   0   0   0
## ASV_574    0   0   0   0   0   0   0   0
## ASV_1728   0   0   0   0   0   1   0   0
## ASV_276    0   0   0   0   0   1   0   0
## ASV_511    0   0   0   0   0   0   0   0
## ASV_1518   0   0   0   0   0   0   0   0
## ASV_171    0   0   0   0   0   0   0   0
## ASV_1373   0   0   0   0   0   0   0   0
## ASV_1078   0   0   0   0   0   0   0   0
## ASV_4258   0   0   0   0   0   0   0   1
## ASV_1336   5   6   6   6  16   9  13   5
## ASV_5356   0   0   0   0   0   2   1   1
## ASV_2174   0   0   0   0   0   0   0   0
## ASV_2658   0   0   0   0   0   0   0   0
## ASV_4109   0   0   0   0   0   0   0   0
## ASV_1947   0   0   0   0   0   0   0   0
## ASV_503    0   0   0   0   0   0   0   0
## ASV_424    0   0   0   0   0   0   0   0
## ASV_2419   0   0   0   0   0   0   0   0
## ASV_2915   0   0   0   0   0   0   0   0
## ASV_4015   0   0   0   0   0   0   0   1
## ASV_4126   0   0   0   0   0   0   0   0
## ASV_3435   0   0   0   0   0   0   0   0
## ASV_2130   0   0   0   0   0   0   0   0
## ASV_4324   6   2   0   0   1   2   2   3
## ASV_4076   2   5   4   4   1   2   1   0
## ASV_5222   0   0   0   0   0   0   0   0
## ASV_4211   0   1   0   0   1   0   0   1
## ASV_3936   0   0   0   0   0   0   0   0
## ASV_3276   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0
## ASV_221    0   0   0   0   0   0   0   0
## ASV_2401   0   0   0   0   0   0   0   0
## ASV_4992   0   0   0   0   0   0   0   0
## ASV_1856   1   0   0   1   0   0   0   0
## ASV_3262   0   0   0   0   0   0   0   0
## ASV_5025   0   0   0   0   1   0   0   0
## ASV_2037   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0
## ASV_5555   0   0   0   1   0   0   0   0
## ASV_3123   0   0   0   0   0   0   0   0
## ASV_2044   0   0   0   0   0   0   0   0
## ASV_4913   1   0   0   0   3   2   1   0
## ASV_1389   0   0   0   0   0   0   0   0
## ASV_3684   3   1   3   5   3   2   1   1
## ASV_901    0   0   0   0   0   0   0   0
## ASV_578    0   0   0   0   0   0   0   0
## ASV_5600   0   0   0   0   0   0   0   0
## ASV_4378   0   1   0   0   0   0   0   0
## ASV_1247   6   6  16   7  16   9  16  11
## ASV_3201   0   0   0   0   0   0   0   0
## ASV_1042   0   0   0   0   0   0   0   0
## ASV_2594   0   0   0   0   0   0   0   0
## ASV_1307   0   0   0   0   0   0   0   0
## ASV_2550   0   0   0   0   0   0   0   1
## ASV_1306   0   1   0   0   0   0   0   0
## ASV_3273   0   0   0   0   0   0   0   0
## ASV_520    0   0   1   0   0   0   0   0
## ASV_3119   0   0   0   0   0   0   0   0
## ASV_5589   0   0   0   0   0   0   0   0
## ASV_2687   3   5   2   6   1   1   1   2
## ASV_4612   0   0   0   0   0   0   0   0
## ASV_5602   2   0   0   0   0   0   0   0
## ASV_499    0   0   0   0   0   0   0   0
## ASV_2617   0   0   0   0   0   0   0   0
## ASV_2770   2   3  10   9  12  10   2   6
## ASV_5521   0   0   1   1   1   1   0   0
## ASV_1658   0   0   0   0   0   0   0   0
## ASV_1213   1   0   0   0   0   0   0   0
## ASV_994    1   0   0   0   0   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   0   0   0   0   0
## ASV_2880   0   0   0   0   0   0   0   0
## ASV_3146   0   0   0   0   0   0   0   0
## ASV_5036   0   0   0   0   0   0   0   0
## ASV_4270   0   0   0   0   0   0   0   0
## ASV_4849   0   0   1   0   0   2   3   0
## ASV_2544   4   5  17  15   7   9  12   9
## ASV_1565   0   0   0   0   0   0   0   0
## ASV_1448  11   7   9   5   5   6   7   4
## ASV_1756   4   2  17   8   5   5   8   8
## ASV_4771   0   0   1   0   0   0   0   0
## ASV_5492   0   0   0   1   2   1   1   0
## ASV_2759   8   5   5   4   1   5   7   7
## ASV_4822   1   0   2   2   0   1   3   1
## ASV_5006   2   1   2   2   1   1   2   2
## ASV_2171   0   0   0   0   0   0   0   0
## ASV_3188   0   0   0   0   0   0   0   0
## ASV_2318   0   0   0   0   0   0   0   0
## ASV_4340   1   3   4   0   0   1   2   2
## ASV_5426   1   2   0   1   2   0   0   1

Although, 131 taxa could not be fit with the model this looks to be due to circumstances where there is very few reads for a particular ASV (thus, a model can’t be fit) or instances where there is only reads in one sample type. See the feature table above.

## [1] 42

## [1] 67

There are 109 ASVs that have no reads in one sample type which is why they aren’t being fit to the model. Another 49 ASVs only have one read per sample type which will not allow them to be fit to the model.

## [1] "In feces, but not in grab samples"

##                                              ASV_713 
##           "Firmicutes_Lachnospiraceae_Coprococcus_3" 
##                                             ASV_1393 
##        "Firmicutes_Lachnospiraceae_Cellulosilyticum" 
##                                              ASV_113 
##    "Firmicutes_Peptostreptococcaceae_Clostridioides" 
##                                              ASV_147 
##  "Firmicutes_Peptostreptococcaceae_Paeniclostridium" 
##                                             ASV_1336 
##     "Proteobacteria_Burkholderiaceae_Parasutterella" 
##                                             ASV_1247 
##    "Actinobacteria_Bifidobacteriaceae_Aeriscardovia" 
##                                             ASV_2770 
##           "Bacteroidetes_Marinifilaceae_Odoribacter" 
##                                             ASV_2544 
## "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-011" 
##                                             ASV_1448 
##            "Firmicutes_Ruminococcaceae_Harryflintia" 
##                                             ASV_1756 
##        "Firmicutes_Ruminococcaceae_Negativibacillus" 
##                                             ASV_2759 
##           "Firmicutes_Ruminococcaceae_Pygmaiobacter"

## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1393   0   0   0   0   0   0   0   0   0   0   0   0   7  19  14   5
##          370 371 372 373 374 375 376 378
## ASV_1393   4  14  26   7   7   5   7   2

## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##         293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_113   0   0   0   0   0   0   0   0   0   0   0   0  33  31  32  47
##         370 371 372 373 374 375 376 378
## ASV_113  69  55 101  85  70  61  78  53

## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   9   8   2   7
##          370 371 372 373 374 375 376 378
## ASV_1448  11   7   9   5   5   6   7   4

## [1] "In grab samples, but not in feces"

##                                              ASV_429 
##           "Firmicutes_Lachnospiraceae_Acetatifactor" 
##                                              ASV_669 
##          "Firmicutes_Lachnospiraceae_Shuttleworthia" 
##                                              ASV_793 
## "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-006" 
##                                              ASV_456 
## "Firmicutes_Veillonellaceae_Veillonellaceae_UCG-001" 
##                                              ASV_171 
##   "Proteobacteria_Succinivibrionaceae_Succinivibrio"

These ASVs couldn’t be fit to the model since there was zero reads in one sample type, but the other sample type has over 50 reads.

Let’s graph the one with the most reads ASV_113 Clostridioides.

Now, we will return to the corncob output. We can see a list of differentially-abundant taxa using:

There are 114 genera differentially abundant. We will look at the unique families they represent.

# of significant genera in each family
Var1	Freq
Firmicutes_Lachnospiraceae	180
Firmicutes_Ruminococcaceae	156
Firmicutes_Christensenellaceae	105
Firmicutes_Family_XIII	30
Bacteroidetes_Rikenellaceae	24
Bacteroidetes_Prevotellaceae	19
Euryarchaeota_Methanobacteriaceae	13
Firmicutes_Erysipelotrichaceae	12
Chloroflexi_Anaerolineaceae	10
Spirochaetes_Spirochaetaceae	10
Actinobacteria_Atopobiaceae	9
Tenericutes	9
Kiritimatiellaeota	8
Actinobacteria_Eggerthellaceae	7
Bacteroidetes_F082	6
Fibrobacteres_Fibrobacteraceae	6
Bacteroidetes_Bacteroidales_BS11_gut_group	3
Firmicutes	3
Firmicutes_Defluviitaleaceae	3
Firmicutes_Peptococcaceae	3
Bacteroidetes	2
Bacteroidetes_Bacteroidaceae	2
Bacteroidetes_p-251-o5	2
Firmicutes_Acidaminococcaceae	2
Firmicutes_Clostridiaceae_1	2
Firmicutes_Eubacteriaceae	2
Firmicutes_Peptostreptococcaceae	2
Patescibacteria	2
Planctomycetes_Pirellulaceae	2
Proteobacteria	2
Proteobacteria_Desulfovibrionaceae	2
Proteobacteria_Succinivibrionaceae	2
Verrucomicrobia_Akkermansiaceae	2
Actinobacteria_Coriobacteriales_Incertae_Sedis	1
Bacteroidetes_Bacteroidales_RF16_group	1
Bacteroidetes_Marinilabiliaceae	1
Bacteroidetes_Muribaculaceae	1
Bacteroidetes_Tannerellaceae	1
Cyanobacteria	1
Elusimicrobia_Elusimicrobiaceae	1
Elusimicrobia_Endomicrobiaceae	1
Firmicutes_Lactobacillaceae	1
Firmicutes_Planococcaceae	1
Firmicutes_Streptococcaceae	1
Firmicutes_Veillonellaceae	1
Proteobacteria_Burkholderiaceae	1
Proteobacteria_Oligoflexaceae	1
Verrucomicrobia	1

This graphs the ASVs in Bacteroidetes differentially abundantant. We do see that Rikenellaceae is lower in abundandance in feces compared grab samples, but we saw this was familiy was higher in relative abundance before so we will double check that.

Statistiscs for Abundance of Akkermansiaceae
	Sample_Type	Genus	mean	sd	sem
56	Feces	Clostridioides	0.6387915	0.1383558	0.0399399
181	Feces	Paeniclostridium	0.4938325	0.2294837	0.0662462
235	Feces	Ruminococcaceae_UCG-005	0.2536037	0.7033963	0.0251856
76	Feces	Dorea	0.2388953	0.1933942	0.0394764
30	Feces	Bacteroides	0.2255830	0.2802845	0.0145321
223	Feces	Romboutsia	0.1954684	0.3827171	0.0390609
281	Feces	Tyzzerella	0.1555427	0.1656968	0.0276161
192	Feces	Phascolarctobacterium	0.1503569	0.0986420	0.0201352
204	Feces	Prevotellaceae_UCG-004	0.1315314	0.3258646	0.0192018
280	Feces	Turicibacter	0.1190462	0.1990139	0.0287252
13	Feces	Alistipes	0.1151407	0.1833281	0.0085851
73	Feces	dgA-11_gut_group	0.0938341	0.1050319	0.0071465
11	Feces	Agathobacter	0.0848349	0.0697738	0.0116290
185	Feces	Parasutterella	0.0813552	0.0391629	0.0113053
109	Feces	Harryflintia	0.0789645	0.0457608	0.0132100
154	Feces	Mailhella	0.0741483	0.1563596	0.0170602
237	Feces	Ruminococcaceae_UCG-009	0.0662564	0.0988824	0.0076289
12	Feces	Akkermansia	0.0600574	0.0750389	0.0046183
7	Feces	Aeriscardovia	0.0600208	0.0601411	0.0122762
169	Feces	Negativibacillus	0.0573690	0.0345288	0.0099676
116	Feces	Incertae_Sedis	0.0542774	0.0704945	0.0117491
23	Feces	Anaerosporobacter	0.0530864	0.0533739	0.0077039
94	Feces	Flavonifractor	0.0528531	0.0427194	0.0037182
283	Feces	Tyzzerella_4	0.0467089	0.0498705	0.0058773
15	Feces	Alloprevotella	0.0453476	0.0862643	0.0071887
61	Feces	Coprococcus_3	0.0437105	0.0564572	0.0057621
103	Feces	GCA-900066225	0.0408701	0.0328104	0.0066974
126	Feces	Lachnoclostridium	0.0407673	0.0495309	0.0101105
241	Feces	Ruminococcaceae_UCG-013	0.0395571	0.0572627	0.0018036
277	Feces	Terrisporobacter	0.0369988	0.0248179	0.0071643
44	Feces	Candidatus_Soleaferrea	0.0360129	0.0477317	0.0068895
222	Feces	Rikenellaceae_RC9_gut_group	0.0356341	0.0859706	0.0015986
160	Feces	Methanocorpusculum	0.0342023	0.0511104	0.0104329
186	Feces	Parvibacter	0.0335902	0.0291808	0.0084238
227	Feces	Ruminiclostridium_5	0.0317005	0.0429588	0.0050627
178	Feces	Oscillibacter	0.0315691	0.0324547	0.0024190
89	Feces	Family_XIII_AD3011_group	0.0305030	0.0680737	0.0032306
234	Feces	Ruminococcaceae_UCG-004	0.0304327	0.0652095	0.0084185
48	Feces	Cellulosilyticum	0.0297891	0.0569408	0.0082187
233	Feces	Ruminococcaceae_UCG-002	0.0291055	0.0567230	0.0038595
239	Feces	Ruminococcaceae_UCG-011	0.0263409	0.0228147	0.0038025
290	Feces	XBB1006	0.0253367	0.0440793	0.0063623
108	Feces	GWE2-31-10	0.0251856	0.0191693	0.0055337
238	Feces	Ruminococcaceae_UCG-010	0.0248479	0.0461817	0.0008570
214	Feces	Pygmaiobacter	0.0245344	0.0192048	0.0039202
184	Feces	Parabacteroides	0.0241291	0.0298835	0.0060999
159	Feces	Methanobrevibacter	0.0236423	0.0618265	0.0037215
226	Feces	Ruminiclostridium_1	0.0214905	0.0556286	0.0060696
225	Feces	Ruminiclostridium	0.0208239	0.0310066	0.0036542
285	Feces	UBA1819	0.0193558	0.0156928	0.0045301
163	Feces	Mogibacterium	0.0193521	0.0581515	0.0040714
114	Feces	Hydrogenoanaerobacterium	0.0193362	0.0197852	0.0025543
174	Feces	Odoribacter	0.0192082	0.0235864	0.0039311
67	Feces	Denitrobacterium	0.0191882	0.0238792	0.0048743
3	Feces	Acetobacter	0.0185080	0.0204518	0.0041747
40	Feces	Campylobacter	0.0182729	0.0266641	0.0054428
57	Feces	Clostridium_sensu_stricto_1	0.0164786	0.0278606	0.0030398
180	Feces	p-1088-a5_gut_group	0.0155396	0.0417214	0.0034768
229	Feces	Ruminiclostridium_9	0.0150709	0.0267372	0.0023272
53	Feces	Christensenellaceae_R-7_group	0.0148646	0.0487342	0.0006503
203	Feces	Prevotellaceae_UCG-003	0.0145027	0.0566721	0.0015390
231	Feces	Ruminococcaceae_NK4A214_group	0.0141766	0.0460014	0.0014076
113	Feces	Hungatella	0.0139791	0.0172950	0.0049926
10	Feces	Aestuariispira	0.0139554	0.0196823	0.0056818
117	Feces	Intestinimonas	0.0139085	0.0113642	0.0032806
133	Feces	Lachnospiraceae_FCS020_group	0.0138013	0.0401638	0.0032157
91	Feces	FD2005	0.0135530	0.0265794	0.0038364
145	Feces	Lachnospiraceae_UCG-010	0.0134737	0.0161588	0.0023323
151	Feces	Lysinibacillus	0.0134573	0.0148229	0.0042790
138	Feces	Lachnospiraceae_NK4A136_group	0.0107925	0.0262609	0.0015474
88	Feces	Faecalibacterium	0.0107498	0.0093950	0.0027121
79	Feces	Elusimicrobium	0.0107198	0.0256244	0.0024657
87	Feces	Eubacterium	0.0103994	0.0101764	0.0029377
137	Feces	Lachnospiraceae_NK3A20_group	0.0103956	0.0594491	0.0019816
293	Feces	NA	0.0103741	0.0392643	0.0002675
236	Feces	Ruminococcaceae_UCG-007	0.0102813	0.0163617	0.0033398
45	Feces	Caproiciproducens	0.0102036	0.0142604	0.0023767
81	Feces	Erysipelatoclostridium	0.0101135	0.0147305	0.0024551
144	Feces	Lachnospiraceae_UCG-009	0.0094588	0.0177503	0.0025620
224	Feces	Roseburia	0.0091183	0.0161287	0.0014723
59	Feces	Coprococcus_1	0.0083048	0.0124823	0.0018017
2	Feces	Acetitomaculum	0.0082661	0.0252547	0.0010634
242	Feces	Ruminococcaceae_UCG-014	0.0078948	0.0214008	0.0005786
60	Feces	Coprococcus_2	0.0078869	0.0143832	0.0023972
217	Feces	Raoultibacter	0.0074416	0.0086101	0.0024855
90	Feces	Family_XIII_UCG-001	0.0073221	0.0186402	0.0020338
36	Feces	Breznakia	0.0072076	0.0091047	0.0026283
96	Feces	Fournierella	0.0071908	0.0085943	0.0017543
74	Feces	Dielma	0.0071292	0.0083068	0.0023980
155	Feces	Marvinbryantia	0.0070862	0.0185011	0.0007962
86	Feces	Escherichia/Shigella	0.0069791	0.0095785	0.0027651
66	Feces	Defluviitaleaceae_UCG-011	0.0069274	0.0173898	0.0015875
245	Feces	Ruminococcus_2	0.0065609	0.0318101	0.0015748
176	Feces	Olsenella	0.0065356	0.0136794	0.0013163
37	Feces	Butyrivibrio	0.0063574	0.0117246	0.0023933
33	Feces	Bilophila	0.0061762	0.0106983	0.0030883
130	Feces	Lachnoclostridium_5	0.0060615	0.0084681	0.0024445
202	Feces	Prevotellaceae_UCG-001	0.0060065	0.0271684	0.0010575
171	Feces	Nitrosomonas	0.0059248	0.0102792	0.0029674
134	Feces	Lachnospiraceae_FE2018_group	0.0057836	0.0098037	0.0020012
25	Feces	Anaerovorax	0.0052314	0.0215634	0.0012706
50	Feces	Cerasicoccus	0.0048723	0.0101461	0.0029289
249	Feces	Sanguibacteroides	0.0048190	0.0065736	0.0018976
111	Feces	hoa5-07d05_gut_group	0.0048156	0.0097705	0.0028205
128	Feces	Lachnoclostridium_10	0.0047588	0.0159617	0.0013893
200	Feces	Prevotellaceae_Ga6A1_group	0.0046212	0.0121785	0.0020297
75	Feces	DNF00809	0.0045312	0.0099781	0.0006441
20	Feces	Anaerofilum	0.0042118	0.0070094	0.0020234
265	Feces	Streptococcus	0.0041349	0.0127466	0.0012265
161	Feces	Methanosphaera	0.0040941	0.0093743	0.0012102
34	Feces	Blautia	0.0038997	0.0121645	0.0007168
80	Feces	Enterococcus	0.0038507	0.0063274	0.0018265
255	Feces	Sellimonas	0.0036649	0.0079158	0.0016158
250	Feces	Sarcina	0.0036622	0.0097637	0.0028185
194	Feces	Pirellula	0.0036374	0.0069816	0.0020154
183	Feces	Papillibacter	0.0034728	0.0115269	0.0008893
282	Feces	Tyzzerella_3	0.0034292	0.0128156	0.0011699
228	Feces	Ruminiclostridium_6	0.0033738	0.0091114	0.0007593
147	Feces	Lactobacillus	0.0032990	0.0089522	0.0008614
83	Feces	Erysipelotrichaceae_UCG-006	0.0032477	0.0074219	0.0015150
27	Feces	Atopobium	0.0027888	0.0079088	0.0006884
262	Feces	Sporobacter	0.0026935	0.0051575	0.0014888
21	Feces	Anaerofustis	0.0026664	0.0049651	0.0007167
64	Feces	CPla-4_termite_group	0.0025267	0.0074154	0.0015137
279	Feces	Treponema_2	0.0024822	0.0156970	0.0004102
46	Feces	Catenisphaera	0.0023699	0.0043432	0.0012538
246	Feces	Saccharofermentans	0.0023208	0.0114662	0.0006620
173	Feces	Ochrobactrum	0.0022955	0.0042134	0.0012163
85	Feces	Erysipelotrichaceae_UCG-009	0.0021437	0.0081140	0.0010475
244	Feces	Ruminococcus_1	0.0021079	0.0089509	0.0002786
230	Feces	Ruminobacter	0.0019248	0.0062992	0.0010499
166	Feces	Mucispirillum	0.0018388	0.0063697	0.0018388
258	Feces	Solobacterium	0.0017884	0.0053905	0.0004921
170	Feces	Neorhizobium	0.0017712	0.0040531	0.0008273
141	Feces	Lachnospiraceae_UCG-002	0.0017172	0.0054352	0.0004529
28	Feces	Aurantimonas	0.0015597	0.0037038	0.0010692
99	Feces	Fusicatenibacter	0.0015533	0.0053807	0.0015533
143	Feces	Lachnospiraceae_UCG-008	0.0014649	0.0055222	0.0002657
100	Feces	Fusobacterium	0.0013048	0.0035323	0.0007210
292	Feces	Z20	0.0012979	0.0044961	0.0012979
172	Feces	Novosphingobium	0.0012785	0.0044289	0.0012785
275	Feces	Taibaiella	0.0012785	0.0044289	0.0012785
43	Feces	Candidatus_Saccharimonas	0.0012466	0.0033976	0.0006935
112	Feces	Howardella	0.0012201	0.0049514	0.0006392
274	Feces	Syntrophococcus	0.0010753	0.0036596	0.0002728
271	Feces	Sutterella	0.0010377	0.0037369	0.0006228
195	Feces	Planococcus	0.0009107	0.0031549	0.0009107
32	Feces	Bifidobacterium	0.0008945	0.0030987	0.0008945
248	Feces	Sanguibacter	0.0008945	0.0030987	0.0008945
135	Feces	Lachnospiraceae_NC2004_group	0.0008615	0.0029843	0.0008615
95	Feces	Flexilinea	0.0008526	0.0036413	0.0001683
132	Feces	Lachnospiraceae_AC2044_group	0.0008081	0.0035506	0.0002237
5	Feces	Actinobacillus	0.0008044	0.0027864	0.0008044
17	Feces	Alysiella	0.0008044	0.0027864	0.0008044
125	Feces	Kocuria	0.0008044	0.0027864	0.0008044
157	Feces	Megasphaera	0.0008016	0.0027768	0.0008016
63	Feces	Corynebacterium_1	0.0007743	0.0026185	0.0003779
198	Feces	possible_genus_Sk018	0.0007410	0.0029886	0.0002876
52	Feces	Chelatococcus	0.0007272	0.0025190	0.0007272
14	Feces	Allobaculum	0.0006879	0.0023828	0.0006879
120	Feces	Jeotgalicoccus	0.0006879	0.0023828	0.0006879
263	Feces	Staphylococcus	0.0006879	0.0023828	0.0006879
266	Feces	Subdoligranulum	0.0006879	0.0023828	0.0006879
220	Feces	Rhodococcus	0.0006684	0.0022656	0.0004625
210	Feces	Pseudochrobactrum	0.0006490	0.0022481	0.0006490
211	Feces	Pseudoclavibacter	0.0006490	0.0022481	0.0006490
162	Feces	Methylobacterium	0.0006425	0.0028343	0.0004724
92	Feces	Fibrobacter	0.0004776	0.0035062	0.0001664
167	Feces	Murdochiella	0.0004597	0.0022520	0.0004597
82	Feces	Erysipelotrichaceae_UCG-004	0.0004415	0.0029695	0.0001470
264	Feces	Stenotrophomonas	0.0004308	0.0021102	0.0004308
209	Feces	Pseudobutyrivibrio	0.0003630	0.0019076	0.0002081
22	Feces	Anaeroplasma	0.0003595	0.0025951	0.0001266
259	Feces	Sphingobacterium	0.0003065	0.0018388	0.0003065
140	Feces	Lachnospiraceae_UCG-001	0.0002982	0.0017890	0.0002982
70	Feces	Desulfovibrio	0.0002802	0.0019098	0.0001473
243	Feces	Ruminococcaceae_V9D2013_group	0.0002605	0.0016139	0.0001292
165	Feces	Moryella	0.0002534	0.0019733	0.0001899
72	Feces	Devosia	0.0002293	0.0013757	0.0002293
97	Feces	Fretibacterium	0.0002293	0.0013757	0.0002293
146	Feces	Lachnospiraceae_XPB1014_group	0.0002248	0.0015558	0.0000864
115	Feces	Hymenobacter	0.0002163	0.0012979	0.0002163
253	Feces	Selenomonas_1	0.0002131	0.0018081	0.0002131
24	Feces	Anaerovibrio	0.0001839	0.0014243	0.0001839
188	Feces	Pedobacter	0.0001839	0.0014243	0.0001839
136	Feces	Lachnospiraceae_ND3007_group	0.0001800	0.0016394	0.0000946
270	Feces	Succinivibrionaceae_UCG-002	0.0001723	0.0013346	0.0001723
41	Feces	Candidatus_Endomicrobium	0.0001518	0.0012880	0.0001518
201	Feces	Prevotellaceae_NK3B31_group	0.0000944	0.0009800	0.0000667
206	Feces	probable_genus_10	0.0000913	0.0011837	0.0000913
38	Feces	Butyrivibrio_2	0.0000912	0.0010955	0.0000482
212	Feces	Pseudomonas	0.0000862	0.0009437	0.0000862
267	Feces	Succiniclasticum	0.0000813	0.0009343	0.0000813
177	Feces	Oribacterium	0.0000536	0.0007652	0.0000536
199	Feces	Prevotella_1	0.0000325	0.0006350	0.0000104
1	Feces	Acetatifactor	0.0000000	0.0000000	0.0000000
4	Feces	Acinetobacter	0.0000000	0.0000000	0.0000000
6	Feces	Aeribacillus	0.0000000	0.0000000	0.0000000
8	Feces	Aerococcus	0.0000000	0.0000000	0.0000000
9	Feces	Aeromicrobium	0.0000000	0.0000000	0.0000000
16	Feces	Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium	0.0000000	0.0000000	0.0000000
18	Feces	Anaerobiospirillum	0.0000000	0.0000000	0.0000000
19	Feces	Anaerocella	0.0000000	0.0000000	0.0000000
26	Feces	Angelakisella	0.0000000	0.0000000	0.0000000
29	Feces	Aureimonas	0.0000000	0.0000000	0.0000000
31	Feces	Bibersteinia	0.0000000	0.0000000	0.0000000
35	Feces	Brevundimonas	0.0000000	0.0000000	0.0000000
39	Feces	CAG-352	0.0000000	0.0000000	0.0000000
42	Feces	Candidatus_Methanomethylophilus	0.0000000	0.0000000	0.0000000
47	Feces	Caviibacter	0.0000000	0.0000000	0.0000000
49	Feces	Cellvibrio	0.0000000	0.0000000	0.0000000
51	Feces	Chelativorans	0.0000000	0.0000000	0.0000000
54	Feces	Chryseobacterium	0.0000000	0.0000000	0.0000000
55	Feces	Clavibacter	0.0000000	0.0000000	0.0000000
58	Feces	Comamonas	0.0000000	0.0000000	0.0000000
62	Feces	Corynebacterium	0.0000000	0.0000000	0.0000000
65	Feces	Curtobacterium	0.0000000	0.0000000	0.0000000
68	Feces	Desemzia	0.0000000	0.0000000	0.0000000
69	Feces	Desulfobulbus	0.0000000	0.0000000	0.0000000
71	Feces	Desulfuromonas	0.0000000	0.0000000	0.0000000
77	Feces	Duganella	0.0000000	0.0000000	0.0000000
78	Feces	Dyadobacter	0.0000000	0.0000000	0.0000000
84	Feces	Erysipelotrichaceae_UCG-008	0.0000000	0.0000000	0.0000000
93	Feces	Filifactor	0.0000000	0.0000000	0.0000000
98	Feces	Frigoribacterium	0.0000000	0.0000000	0.0000000
101	Feces	Galbitalea	0.0000000	0.0000000	0.0000000
102	Feces	Gallicola	0.0000000	0.0000000	0.0000000
104	Feces	GCA-900066575	0.0000000	0.0000000	0.0000000
105	Feces	Gillisia	0.0000000	0.0000000	0.0000000
106	Feces	Gilvimarinus	0.0000000	0.0000000	0.0000000
107	Feces	Glutamicibacter	0.0000000	0.0000000	0.0000000
110	Feces	Helcococcus	0.0000000	0.0000000	0.0000000
118	Feces	Janthinobacterium	0.0000000	0.0000000	0.0000000
119	Feces	Jeotgalibaca	0.0000000	0.0000000	0.0000000
121	Feces	Kandleria	0.0000000	0.0000000	0.0000000
122	Feces	Ketogulonicigenium	0.0000000	0.0000000	0.0000000
123	Feces	Kineococcus	0.0000000	0.0000000	0.0000000
124	Feces	Klebsiella	0.0000000	0.0000000	0.0000000
127	Feces	Lachnoclostridium_1	0.0000000	0.0000000	0.0000000
129	Feces	Lachnoclostridium_12	0.0000000	0.0000000	0.0000000
131	Feces	Lachnospira	0.0000000	0.0000000	0.0000000
139	Feces	Lachnospiraceae_NK4B4_group	0.0000000	0.0000000	0.0000000
142	Feces	Lachnospiraceae_UCG-006	0.0000000	0.0000000	0.0000000
148	Feces	Leptotrichia	0.0000000	0.0000000	0.0000000
149	Feces	Leucobacter	0.0000000	0.0000000	0.0000000
150	Feces	Limnohabitans	0.0000000	0.0000000	0.0000000
152	Feces	M2PT2-76_termite_group	0.0000000	0.0000000	0.0000000
153	Feces	Macellibacteroides	0.0000000	0.0000000	0.0000000
156	Feces	Massilia	0.0000000	0.0000000	0.0000000
158	Feces	Methanimicrococcus	0.0000000	0.0000000	0.0000000
164	Feces	Moraxella	0.0000000	0.0000000	0.0000000
168	Feces	Mycoplasma	0.0000000	0.0000000	0.0000000
175	Feces	Oligella	0.0000000	0.0000000	0.0000000
179	Feces	Oscillospira	0.0000000	0.0000000	0.0000000
182	Feces	Pantoea	0.0000000	0.0000000	0.0000000
187	Feces	Parvimonas	0.0000000	0.0000000	0.0000000
189	Feces	Pelospora	0.0000000	0.0000000	0.0000000
190	Feces	Peptococcus	0.0000000	0.0000000	0.0000000
191	Feces	Peptoniphilus	0.0000000	0.0000000	0.0000000
193	Feces	Pigmentiphaga	0.0000000	0.0000000	0.0000000
196	Feces	Pontibacter	0.0000000	0.0000000	0.0000000
197	Feces	Porphyromonas	0.0000000	0.0000000	0.0000000
205	Feces	Prevotellaceae_YAB2003_group	0.0000000	0.0000000	0.0000000
207	Feces	Proteiniclasticum	0.0000000	0.0000000	0.0000000
208	Feces	Proteiniphilum	0.0000000	0.0000000	0.0000000
213	Feces	Psychrobacter	0.0000000	0.0000000	0.0000000
215	Feces	Pyramidobacter	0.0000000	0.0000000	0.0000000
216	Feces	Quinella	0.0000000	0.0000000	0.0000000
218	Feces	Rathayibacter	0.0000000	0.0000000	0.0000000
219	Feces	Rhodobacter	0.0000000	0.0000000	0.0000000
221	Feces	Rikenella	0.0000000	0.0000000	0.0000000
232	Feces	Ruminococcaceae_UCG-001	0.0000000	0.0000000	0.0000000
240	Feces	Ruminococcaceae_UCG-012	0.0000000	0.0000000	0.0000000
247	Feces	Salana	0.0000000	0.0000000	0.0000000
251	Feces	Schwartzia	0.0000000	0.0000000	0.0000000
252	Feces	Sediminispirochaeta	0.0000000	0.0000000	0.0000000
254	Feces	Selenomonas_4	0.0000000	0.0000000	0.0000000
256	Feces	Shuttleworthia	0.0000000	0.0000000	0.0000000
257	Feces	Slackia	0.0000000	0.0000000	0.0000000
260	Feces	Sphingobium	0.0000000	0.0000000	0.0000000
261	Feces	Sphingomonas	0.0000000	0.0000000	0.0000000
268	Feces	Succinimonas	0.0000000	0.0000000	0.0000000
269	Feces	Succinivibrio	0.0000000	0.0000000	0.0000000
272	Feces	Suttonella	0.0000000	0.0000000	0.0000000
273	Feces	Synergistes	0.0000000	0.0000000	0.0000000
276	Feces	Tannerella	0.0000000	0.0000000	0.0000000
278	Feces	Thermomonas	0.0000000	0.0000000	0.0000000
284	Feces	U29-B03	0.0000000	0.0000000	0.0000000
286	Feces	Variovorax	0.0000000	0.0000000	0.0000000
287	Feces	Veillonellaceae_UCG-001	0.0000000	0.0000000	0.0000000
288	Feces	Verticia	0.0000000	0.0000000	0.0000000
289	Feces	Weissella	0.0000000	0.0000000	0.0000000
291	Feces	Xylophilus	0.0000000	0.0000000	0.0000000

Statistiscs for Abundance of Rikenellaceae
	Sample_Type	Genus	mean	sd	sem
9	Feces	Alistipes	0.1151407	0.1833281	0.0085851
11	Feces	dgA-11_gut_group	0.0938341	0.1050319	0.0071465
14	Feces	Rikenellaceae_RC9_gut_group	0.0356341	0.0859706	0.0015986
16	Feces	NA	0.0321720	0.0516502	0.0066680
38	Solid	Rikenellaceae_RC9_gut_group	0.0305544	0.0893249	0.0016610
6	Grab Sample	Rikenellaceae_RC9_gut_group	0.0293962	0.0865592	0.0016096
22	Stomach Tube	Rikenellaceae_RC9_gut_group	0.0287573	0.0782038	0.0014542
46	Liquid Unstrained	Rikenellaceae_RC9_gut_group	0.0240750	0.0592204	0.0013487
39	Solid	U29-B03	0.0202607	0.0140115	0.0028601
30	Liquid Strained	Rikenellaceae_RC9_gut_group	0.0195953	0.0571284	0.0010623
7	Grab Sample	U29-B03	0.0176858	0.0225679	0.0046067
23	Stomach Tube	U29-B03	0.0087306	0.0104589	0.0021349
47	Liquid Unstrained	U29-B03	0.0079824	0.0112709	0.0028177
12	Feces	hoa5-07d05_gut_group	0.0048156	0.0097705	0.0028205
44	Liquid Unstrained	hoa5-07d05_gut_group	0.0040984	0.0076867	0.0027177
31	Liquid Strained	U29-B03	0.0040380	0.0078627	0.0016050
4	Grab Sample	hoa5-07d05_gut_group	0.0032071	0.0077284	0.0022310
32	Liquid Strained	NA	0.0017208	0.0065606	0.0008470
28	Liquid Strained	hoa5-07d05_gut_group	0.0015568	0.0042730	0.0012335
40	Solid	NA	0.0015567	0.0064352	0.0008308
48	Liquid Unstrained	NA	0.0015525	0.0054636	0.0008639
5	Grab Sample	Rikenella	0.0014625	0.0050663	0.0014625
42	Liquid Unstrained	Anaerocella	0.0012392	0.0035050	0.0012392
24	Stomach Tube	NA	0.0012366	0.0054721	0.0007064
20	Stomach Tube	hoa5-07d05_gut_group	0.0012348	0.0042773	0.0012348
45	Liquid Unstrained	Rikenella	0.0009321	0.0026365	0.0009321
26	Liquid Strained	Anaerocella	0.0007805	0.0027037	0.0007805
8	Grab Sample	NA	0.0007000	0.0038342	0.0004950
37	Solid	Rikenella	0.0006256	0.0021671	0.0006256
41	Liquid Unstrained	Alistipes	0.0003632	0.0023145	0.0001327
43	Liquid Unstrained	dgA-11_gut_group	0.0002380	0.0017008	0.0001417
17	Stomach Tube	Alistipes	0.0002040	0.0018299	0.0000857
25	Liquid Strained	Alistipes	0.0001770	0.0011256	0.0000527
1	Grab Sample	Alistipes	0.0001556	0.0016626	0.0000779
35	Solid	dgA-11_gut_group	0.0001345	0.0011416	0.0000777
27	Liquid Strained	dgA-11_gut_group	0.0001136	0.0010386	0.0000707
33	Solid	Alistipes	0.0000872	0.0009282	0.0000435
3	Grab Sample	dgA-11_gut_group	0.0000813	0.0011941	0.0000813
19	Stomach Tube	dgA-11_gut_group	0.0000686	0.0010082	0.0000686
2	Grab Sample	Anaerocella	0.0000000	0.0000000	0.0000000
10	Feces	Anaerocella	0.0000000	0.0000000	0.0000000
13	Feces	Rikenella	0.0000000	0.0000000	0.0000000
15	Feces	U29-B03	0.0000000	0.0000000	0.0000000
18	Stomach Tube	Anaerocella	0.0000000	0.0000000	0.0000000
21	Stomach Tube	Rikenella	0.0000000	0.0000000	0.0000000
29	Liquid Strained	Rikenella	0.0000000	0.0000000	0.0000000
34	Solid	Anaerocella	0.0000000	0.0000000	0.0000000
36	Solid	hoa5-07d05_gut_group	0.0000000	0.0000000	0.0000000

From these graphs we can see that Rikenellaceae_RC9_gut_group appears to be higher in feces there is also other genera (Alistipes,dgA_11_gut_group) in the Rikenellaceae family that cause the overall relative abundance of this family to be higher than in grab samples. However, there are certain ASVs in Rikenellaceae that are significantly lower in feces. This backs up the corncob data.

Genera in Firmicutes differentially abundantant between feces and grab samples.

# of Significant ASVs by Phyla
Var1	Freq
Firmicutes	504
Bacteroidetes	62
Actinobacteria	17
Euryarchaeota	13
Chloroflexi	10
Spirochaetes	10
Tenericutes	9
Kiritimatiellaeota	8
Proteobacteria	8
Fibrobacteres	6
Verrucomicrobia	3
Elusimicrobia	2
Patescibacteria	2
Planctomycetes	2
Cyanobacteria	1

While the most common phyla to have significant differentially abundant taxa were Firmicutes and Bacteroidetes this could be because they are the most dominant taxa rather than really being “more important” in distinguishing sample types.

# of Significant ASVs by Phyla
Phylum	#Significant ASVs	Total ASVs	Percent Significant ASVs
Actinobacteria	17	96	17.708333
Bacteroidetes	62	1257	4.932379
Chloroflexi	10	39	25.641026
Cyanobacteria	1	65	1.538461
Elusimicrobia	2	16	12.500000
Euryarchaeota	13	44	29.545455
Fibrobacteres	6	39	15.384615
Firmicutes	504	3095	16.284330
Kiritimatiellaeota	8	180	4.444444
Patescibacteria	2	14	14.285714
Planctomycetes	2	15	13.333333
Proteobacteria	8	219	3.652968
Spirochaetes	10	138	7.246377
Tenericutes	9	188	4.787234
Verrucomicrobia	3	35	8.571429
Deferribacteres	0	1	0.000000
Epsilonbacteraeota	0	2	0.000000
Fusobacteria	0	4	0.000000
Gemmatimonadetes	0	1	0.000000
Lentisphaerae	0	31	0.000000
Synergistetes	0	6	0.000000

This table shows that while Firmicutes and Bacteroidetes are the most common phyla to have differentially abundant taxa this is in part due the fact that they are the most prevelant phyla. As a percent Chloroflexi and Euryarcheota are more common.

We will graph out the significantly different taxa from these phylums.

Here we can see that the Euryarchaeota that are important for telling samples types apart are all methogens. Feces has a strong negative effect on most of these methanogens (methogens are lower in feces). Interestingly, fecal samples have lower Flexilinea.

## [1] "Flexilinea"

## OTU Table:          [38 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_3963   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1206   2   0   2   1   1   6   0   0   0   0   0   2   0   0   0   0
## ASV_1519   0   1   0   3   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_1003   2   1   1   2   2   1   2   2   1   1   2   2   0   0   0   0
## ASV_3326   0   0   1   0   1   0   1   0   0   0   1   0   0   0   0   0
## ASV_1572   0   0   3   2   2   3   2   0   3   0   0   0   0   0   0   0
## ASV_1315   1   0   1   1   1   3   1   1   2   0   0   0   0   0   1   0
## ASV_3266   0   2   1   0   2   1   0   0   0   0   1   0   0   0   0   0
## ASV_727    2   0   3   2   0   4   4   1   1   3   2   4   0   1   0   0
## ASV_2479   0   0   0   0   3   0   0   1   1   0   0   2   0   1   0   0
## ASV_1570   1   0   0   1   2   1   0   0   2   0   2   0   0   0   0   1
## ASV_1257   0   0   0   1   1   0   1   0   2   0   0   0   0   0   0   0
## ASV_1826   1   1   0   2   0   2   0   1   0   0   1   0   0   0   0   0
## ASV_4222   0   2   0   1   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_612    1   1   1   3   1   3   0   1   2   0   2   1   0   0   0   1
## ASV_2625   1   0   0   0   0   0   1   1   1   2   0   0   0   0   0   0
## ASV_3203   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2739   3   0   0   0   0   0   0   0   0   0   2   1   0   0   0   0
## ASV_3861   0   0   0   1   0   0   1   2   1   0   0   0   0   0   0   0
## ASV_3258   0   0   0   6   2   1   0   0   0   0   0   0   0   0   0   0
## ASV_2612   0   2   0   4   0   0   0   0   0   1   1   0   0   0   0   0
## ASV_1761   0   0   1   2   0   1   0   0   1   0   1   1   0   0   0   0
## ASV_2122   0   1   0   2   1   1   0   1   1   0   1   1   0   0   0   0
## ASV_1879   0   0   0   1   2   0   2   3   1   0   5   0   0   0   0   0
## ASV_2100   0   2   2   1   0   1   1   1   0   1   1   0   0   0   1   0
## ASV_409    6   4   4   8   3   7   8   2   5   3   3   2   0   0   0   0
## ASV_4093   0   1   0   0   0   1   0   1   1   0   0   0   0   0   0   0
## ASV_2353   0   0   0   1   0   0   1   0   1   1   0   4   0   0   0   0
## ASV_594    2   1   2   3   1   2   6   3   3   6   6   7   2   0   1   0
## ASV_2831   0   1   0   0   0   0   0   1   0   0   2   1   0   0   0   0
## ASV_743    2   0   1   2   0   1   6   5   6   1   2   2   0   0   0   0
## ASV_1877   0   1   0   0   0   1   1   1   1   0   1   0   0   0   0   0
## ASV_1428   2   3   0   0   1   1   2   4   0   0   0   0   0   1   0   0
## ASV_1620   1   1   1   2   1   2   1   2   0   1   1   1   0   0   0   0
## ASV_4680   0   0   0   0   0   1   0   0   0   0   1   0   0   0   0   0
## ASV_2984   3   0   1   1   1   0   0   0   0   0   0   1   0   0   0   0
## ASV_3303   0   2   0   1   1   0   0   0   0   0   2   1   0   0   0   0
## ASV_3402   0   0   0   2   1   1   0   0   0   1   2   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_3963   0   0   0   0   1   0   0   0
## ASV_1206   0   2   0   0   0   0   0   0
## ASV_1519   0   1   0   0   0   0   1   0
## ASV_1003   0   0   1   0   0   0   0   0
## ASV_3326   0   0   0   0   0   0   0   0
## ASV_1572   0   0   0   0   0   0   0   0
## ASV_1315   0   0   0   0   0   0   1   0
## ASV_3266   0   0   0   1   0   0   0   0
## ASV_727    2   0   1   1   1   1   0   0
## ASV_2479   0   0   0   0   0   0   0   0
## ASV_1570   0   0   0   0   0   0   0   0
## ASV_1257   0   0   0   0   0   0   0   0
## ASV_1826   0   0   0   0   0   0   0   0
## ASV_4222   0   0   0   0   0   0   0   0
## ASV_612    1   0   0   0   0   0   0   0
## ASV_2625   0   0   0   0   0   0   0   0
## ASV_3203   0   0   0   0   0   0   0   0
## ASV_2739   0   0   0   0   0   1   0   0
## ASV_3861   0   0   0   0   0   0   0   0
## ASV_3258   0   0   0   0   0   0   0   0
## ASV_2612   0   0   0   0   0   0   0   0
## ASV_1761   1   0   0   0   0   0   0   0
## ASV_2122   0   0   0   0   0   0   0   0
## ASV_1879   0   0   0   1   1   0   0   0
## ASV_2100   0   0   0   0   0   0   0   2
## ASV_409    0   0   0   0   0   0   0   1
## ASV_4093   0   0   0   0   0   0   0   0
## ASV_2353   0   0   0   0   0   0   0   0
## ASV_594    0   0   0   0   1   0   0   0
## ASV_2831   0   0   0   0   0   0   0   0
## ASV_743    0   0   0   0   0   0   0   0
## ASV_1877   0   1   0   0   0   0   0   0
## ASV_1428   0   0   0   0   0   0   0   0
## ASV_1620   0   0   0   0   0   0   0   0
## ASV_4680   0   0   0   0   0   0   0   0
## ASV_2984   0   0   0   0   0   0   0   0
## ASV_3303   0   0   0   0   0   0   0   0
## ASV_3402   0   0   0   0   0   0   0   0

## [1] 20

Flexilinea is the only Genus found in the phylum Chloroflexi in this data set. It also seems like there are a number of ASVs that don’t have an reads in fecal samples. Let’s look at the ASV level.

We will look into Euryarchaeota ASVs a bit more now.

## [1] 12

##                                                                                                               ASV_1308 
##                      "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter" 
##                                                                                                               ASV_3184 
##                          "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera" 
##                                                                                                                ASV_484 
##                      "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter" 
##                                                                                                               ASV_3936 
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae_Candidatus_Methanomethylophilus" 
##                                                                                                                ASV_231 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_3478 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                                ASV_657 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_2010 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_2978 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_2521 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_3242 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_3537 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"

## OTU Table:          [12 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_3936   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_231   13   3   1   5   7   3   8  15   7   3   4   5   0   0   0   0
## ASV_3478   1   1   0   0   0   1   0   0   0   1   1   0   0   0   0   0
## ASV_657    1   0   0   1   1   1   2   1   3   0   3   0   0   0   0   0
## ASV_2010   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1584   0   0   0   0   0   0   4   0   0   0   0   0   0   0   2   0
## ASV_2978   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1603   0   2   1   0   1   2   0   0   0   0   1   0   0   0   0   0
## ASV_2521   0   0   1   0   0   0   1   0   0   2   0   0   0   0   0   0
## ASV_3242   1   0   1   1   0   0   1   0   0   0   1   1   0   0   0   0
## ASV_3537   0   0   0   0   1   1   0   0   0   0   0   0   0   0   0   0
## ASV_3875   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_3936   0   0   0   0   0   0   0   0
## ASV_231    0   0   0   0   0   0   0   0
## ASV_3478   0   0   0   0   0   0   0   0
## ASV_657    0   0   0   0   0   0   0   0
## ASV_2010   0   0   0   0   0   0   0   0
## ASV_1584   0   0   0   0   0   0   0   0
## ASV_2978   0   0   0   0   0   0   0   0
## ASV_1603   0   1   0   0   0   0   0   0
## ASV_2521   0   0   0   0   0   0   0   0
## ASV_3242   0   0   0   0   0   0   0   0
## ASV_3537   0   0   0   0   0   0   0   0
## ASV_3875   0   0   0   1   0   0   0   0

## OTU Table:          [2 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1434   0   0   0   0   0   0   0   0   0   0   0   0   0   0   4  18
## ASV_4298   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_1434   3   5   4   5   5   9   7  21
## ASV_4298   0   1   2   0   1   0   0   0

There are increased amounts of Methanocorpusculum in one ASV, but the other ASV has low amounts so it seems like not a strong enough association to bring this up.

Based on the DPCoA the phyla Spirochaetes and Actinobacteria also play and important role in distinguishing feces from grab samples.

# of Significant ASVs by Phyla
Var1	Freq
Firmicutes_Lachnospiraceae	32
Firmicutes_Ruminococcaceae	23
Bacteroidetes_Prevotellaceae	7
Firmicutes_Erysipelotrichaceae	7
Firmicutes_Family_XIII	4
Bacteroidetes_Rikenellaceae	3
Actinobacteria_Atopobiaceae	2
Actinobacteria_Eggerthellaceae	2
Euryarchaeota_Methanobacteriaceae	2
Firmicutes_Acidaminococcaceae	2
Firmicutes_Veillonellaceae	2
Planctomycetes_Pirellulaceae	2
Proteobacteria_Desulfovibrionaceae	2
Proteobacteria_Succinivibrionaceae	2
Actinobacteria_Coriobacteriales_Incertae_Sedis	1
Actinobacteria_Corynebacteriaceae	1
Bacteroidetes_Bacteroidaceae	1
Bacteroidetes_Tannerellaceae	1
Chloroflexi_Anaerolineaceae	1
Elusimicrobia_Elusimicrobiaceae	1
Elusimicrobia_Endomicrobiaceae	1
Epsilonbacteraeota_Campylobacteraceae	1
Euryarchaeota_Methanocorpusculaceae	1
Fibrobacteres_Fibrobacteraceae	1
Firmicutes_Christensenellaceae	1
Firmicutes_Clostridiaceae_1	1
Firmicutes_Defluviitaleaceae	1
Firmicutes_Eubacteriaceae	1
Firmicutes_Peptostreptococcaceae	1
Firmicutes_Streptococcaceae	1
Proteobacteria_Burkholderiaceae	1
Proteobacteria_Devosiaceae	1
Spirochaetes_Spirochaetaceae	1
Synergistetes_Synergistaceae	1
Tenericutes_Anaeroplasmataceae	1
Verrucomicrobia_Akkermansiaceae	1

From this we can see that Lachnospiraceae, Ruminococcaceae, Prevotellaceae and Erysipelotrichaceae were the most common families to be differentially abundant in feces compared to grab samples. We will take a closer look at all ASVs differentially abundant.

Differentially Abundant Taxa
	p_value	ASV	Taxa
1	1.51e-03	ASV_1	Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group
2	1.51e-03	ASV_10	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans
3	1.51e-03	ASV_1006	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Candidatus_Soleaferrea
4	1.51e-03	ASV_1014	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax
5	1.51e-03	ASV_1016	Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis
6	1.51e-03	ASV_103	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1
7	1.51e-03	ASV_105	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group
8	1.51e-03	ASV_1098	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014
10	1.51e-03	ASV_1118	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_4
11	1.51e-03	ASV_1130	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018
12	1.51e-03	ASV_1132	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group
13	1.51e-03	ASV_1169	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Syntrophococcus
15	1.51e-03	ASV_1220	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_5
16	1.51e-03	ASV_1221	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium
17	1.51e-03	ASV_124	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group
18	1.51e-03	ASV_1256	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group
20	1.51e-03	ASV_13	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group
21	1.51e-03	ASV_1325	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
23	1.51e-03	ASV_14	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium
25	1.51e-03	ASV_149	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio
26	1.51e-03	ASV_1563	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium
28	1.51e-03	ASV_168	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Turicibacter
29	1.51e-03	ASV_1682	Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1
30	1.51e-03	ASV_1688	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_GCA-900066225
31	1.51e-03	ASV_172	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809
32	1.51e-03	ASV_184	Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera
33	1.51e-03	ASV_1882	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia
35	1.51e-03	ASV_199	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella
36	1.51e-03	ASV_2	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group
37	1.51e-03	ASV_201	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group
38	1.51e-03	ASV_204	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Dorea
41	1.51e-03	ASV_210	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10
42	1.51e-03	ASV_2189	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001
43	1.51e-03	ASV_22	Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella
46	1.51e-03	ASV_227	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella
47	1.51e-03	ASV_23	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1
50	1.51e-03	ASV_235	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1
52	1.51e-03	ASV_246	Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma
53	1.51e-03	ASV_247	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-009
54	1.51e-03	ASV_25	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio
55	1.51e-03	ASV_254	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010
57	1.51e-03	ASV_26	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004
58	1.51e-03	ASV_267	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013
60	1.51e-03	ASV_3	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005
61	1.51e-03	ASV_3005	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Hydrogenoanaerobacterium
63	1.51e-03	ASV_311	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella
64	1.51e-03	ASV_320	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10
65	1.51e-03	ASV_330	Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae_Akkermansia
66	1.51e-03	ASV_335	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_dgA-11_gut_group
67	1.51e-03	ASV_344	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group
68	1.51e-03	ASV_348	Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011
69	1.51e-03	ASV_357	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002
70	1.51e-03	ASV_36	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae_Bacteroides
71	1.51e-03	ASV_37	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter
73	1.51e-03	ASV_376	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group
77	1.51e-03	ASV_409	Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea
78	1.51e-03	ASV_418	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium
79	1.51e-03	ASV_442	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Phascolarctobacterium
81	1.51e-03	ASV_457	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008
82	1.51e-03	ASV_471	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium
83	1.51e-03	ASV_48	Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae_Romboutsia
84	1.51e-03	ASV_510	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Alloprevotella
85	1.51e-03	ASV_52	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1
86	1.51e-03	ASV_524	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002
88	1.51e-03	ASV_560	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6
90	1.51e-03	ASV_57	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia
91	1.51e-03	ASV_60	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Alistipes
92	1.51e-03	ASV_601	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009
93	1.51e-03	ASV_622	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium
94	1.51e-03	ASV_656	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter
96	1.51e-03	ASV_674	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera
97	1.51e-03	ASV_68	Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter
98	1.51e-03	ASV_7	Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter
99	1.51e-03	ASV_71	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2
100	1.51e-03	ASV_724	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Incertae_Sedis
102	1.51e-03	ASV_783	Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_p-1088-a5_gut_group
103	1.51e-03	ASV_795	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001
104	1.51e-03	ASV_8	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum
106	1.51e-03	ASV_815	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
107	1.51e-03	ASV_819	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Flavonifractor
108	1.51e-03	ASV_837	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Agathobacter
109	1.51e-03	ASV_886	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group
111	1.51e-03	ASV_90	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella
112	1.51e-03	ASV_902	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002
113	1.51e-03	ASV_953	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group
114	1.51e-03	ASV_963	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Anaerosporobacter
9	2.77e-03	ASV_1100	Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium
14	2.77e-03	ASV_117	Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus
19	2.77e-03	ASV_1258	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-006
27	2.77e-03	ASV_1615	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006
80	2.77e-03	ASV_450	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter
87	2.77e-03	ASV_534	Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae_Devosia
95	2.77e-03	ASV_66	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum
110	2.77e-03	ASV_893	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Oscillibacter
59	4.06e-03	ASV_29	Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_Treponema_2
101	4.06e-03	ASV_757	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_1
22	4.96e-03	ASV_1366	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio
24	4.96e-03	ASV_1434	Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae_Methanocorpusculum
40	4.96e-03	ASV_2079	Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae_Campylobacter
44	4.96e-03	ASV_2217	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae_Parabacteroides
49	4.96e-03	ASV_2319	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Fusicatenibacter
51	4.96e-03	ASV_2357	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Sporobacter
56	4.96e-03	ASV_2540	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_Denitrobacterium
74	4.96e-03	ASV_3830	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelatoclostridium
105	4.96e-03	ASV_80	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group
76	7.30e-03	ASV_3930	Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Fretibacterium
89	7.30e-03	ASV_563	Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae_Candidatus_Endomicrobium
48	1.31e-02	ASV_2306	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-001
75	1.31e-02	ASV_3902	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_UBA1819
34	1.88e-02	ASV_1915	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_FD2005
45	1.88e-02	ASV_2220	Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_Pirellula
62	1.97e-02	ASV_303	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003
72	2.30e-02	ASV_3758	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Caproiciproducens
39	2.62e-02	ASV_2068	Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium_1

These are taxa that are differentailly abundant between grab samples and feces and their false discovery corrected p-value. ASVs are listed by significance.

## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##       293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369 370
## ASV_1 114 124 177 280 224 295 298 281 230 204 170 216   4   8   4   7   8
##       371 372 373 374 375 376 378
## ASV_1   8   6   5   9   4   0   1

## 
## Call:
## bbdml(formula = ASV_1 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = ps_sub_gen)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value         Pr(>|t|)    
## (Intercept)      -1.47780    0.07625 -19.380 0.00000000000155 ***
## Sample_TypeFeces -0.95570    0.06216 -15.375 0.00000000005273 ***
## CowIDCow_2477     0.18844    0.08258   2.282           0.0365 *  
## CowIDCow_2549    -0.05694    0.08660  -0.657           0.5202    
## CowIDCow_796      0.15162    0.08276   1.832           0.0856 .  
## DayDay_7         -0.07839    0.07259  -1.080           0.2962    
## DayDay_9          0.04504    0.07120   0.633           0.5359    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value        Pr(>|t|)    
## (Intercept)   -6.089      0.312  -19.52 0.0000000000014 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -143.94

This is the feature table for ASV_1, let’s graph out this most significantly differentially abundant ASV Christensenellaceae_R-7_group. There is significantly less of this taxa in feces compared to grab samples. The day did not effect this, but there was significant cow differences in abundance.

Here we see that Christensenellaceae_R-7_group is more abundant in feces vs grab samples. In fact if we look at the feature table above we see this taxa is almost not present in the rumen grab samples.

Grab Samples vs other rumen samples

We will remove other a few sample types to compress the data down and look just at the grab sample and stomach tube.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 4690 taxa and 56 samples ]
## sample_data() Sample Data:       [ 56 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 4690 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 4690 tips and 4688 internal nodes ]

After subsetting the data we have 4,690 ASVs in 56 samples.

Metrics after filtering

## [1] 4690

## [1] 20

## [1] 74

## [1] 110

## [1] 279

Previously, there are 5485 ASVs in the dataset. This was composed of 21 phyla, 78 Orders, 116 Families and 293 Genera. In the new subset we have 4690 ASVs in the dataset. This is composed of 20 phyla, 74 Orders, 110 Families and 279 Genera.

Exploratory Analysis

Again we will transformed the data for some exploratory analysis.

## Scale for 'colour' is already present. Adding another scale for
## 'colour', which will replace the existing scale.

Here we begin to see that Stomach Tube samples are more variable than the grab sample. Liquid strained samples seem to be the most variable (maybe comprable to stomach tube samples). Additionally, there seems to be two clusters for stomach tube samples (it’s probably not significant though). Potentially due to the presence of fiber in the sample or not?

From the eigenvalues we can see that 2 axis is appropriate for graphing, together explaining almost 90% of the variance between the samples.

Now that we take into account phylogenetic information in the distance metric there is a lot more variation explained. The first Axsis contains more variation that the second and mostly separates liquid (strained and unstrained) and some stomach tube samples from solid and grab samples.

Let’s make a figure with Weighted unifrac with and without the fecal samples

The eigenvalues here show the variation is spread across many axis, thus a 3D graph is best. You can find it hosted online here.

## No trace type specified:
##   Based on info supplied, a 'scatter3d' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter3d

## No scatter3d mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode

As before less of the variation is explained in each axis with the unweighted versus the weighted unifrac. Thus it seems that the difference between sample types is due to abundance differences and less about differences in species. We also, see the two clusters of stomach tube samples appearing again. This strengthens the hypothesis that stomach tube samples are more variable than grab samples and that there a minor taxa that explain differences between stomach tube samples. Addtionally, it looks like the two clusters of stomach tube samples might be forming due to individual cow differences (not a breed difference). Liquid sample remain different from grab and stomach tube samples.

The eigenvalues here show 2 axis are sufficient to capture most of the total variation.

We see again that the 1st axis corresponds is separtating liquid strained and unstrained samples from other rumen samples. This plot suggest there are more Bacteroidetes and Kiritimatiellaeota in the liquid samples, while rumen samples have more Firmicutes. This can also be seen in the first DPCoA we made where we said that Liquid samples have more Bacteroidetes and less Firmicutes than other rumen sample types. Thus, we will probably only need to have one DPCoA graph in the paper.

We should see what taxa are differentially more or less abundant in grab sample vs other rumen sample types.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 278 taxa and 56 samples ]
## sample_data() Sample Data:       [ 56 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 278 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 278 tips and 277 internal nodes ]

There are 278 genera in the rumen sample types.

99 taxa could not be fit with the model, but 179 were fit to the model and 108 were significantly differentially abundant genera p<0.05. 87 were significantly differentially abundant genera p<0.01. Lastly, 87 were significantly differentially abundant taxa p<0.05.

First, we will check if into the genera could not be fit to the model and see if we can determine why.

## OTU Table:          [99 taxa and 56 samples]
##                      taxa are rows
##          282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_5569   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_204    0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4099   1   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_878    4   9   0   0   2   0   0   0   1   2   1   6   5   4   0   0
## ASV_5218   0   1   0   1   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_724    0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_5230   0   0   0   2   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5009   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_2417   2   1   2   2   1   0   0   0   0   0   1   0   0   1   0   0
## ASV_2322   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_113    0   0   2   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5397   0   0   0   0   0   0   0   3   2   0   2   0   0   0   0   0
## ASV_4951   0   1   1   1   0   0   2   4   0   0   0   0   0   0   0   0
## ASV_5246   0   0   0   0   0   0   0   0   2   0   0   0   0   0   0   0
## ASV_4383   0   0   1   0   2   0   1   1   2   2   0   0   0   0   1   2
## ASV_5288   0   2   0   0   1   0   0   0   0   0   1   0   0   0   1   2
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1258   1   4   1   0   3   3   1   0  11   1   1   1   1   1   2   2
## ASV_5496   2   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_4673   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3469   1   0   0   0   0   1   1   1   0   0   0   0   0   1   0   0
## ASV_4670   0   2   1   0   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4857   0   1   5   0   0   1   2   0   2   0   0   0   0   0   0   0
## ASV_5547   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4998   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4508   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_2399   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5206   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   0   0   3   0   0   1   0   0   0   0   0   0   0   1   0   0
## ASV_1078   0   5   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4258   1   1   8   2   2   1   0   0   1   0   1   0   0   0   0   0
## ASV_2658   0   0   0   0   0   0   1   0   0   0   0   0   0   1   0   0
## ASV_2389   2   1   0   1   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_1853   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4912   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5382   0   0   0   3   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2915   0   0  16   4   5   3   1   1   0   0   0   0   0   0   1   0
## ASV_4015   1   0   0   1   5   1   1   1   2   2   0   1   0   1   0   0
## ASV_4126   0   0   3   3   0   0   0   0   0   0   0   0   0   0   0   2
## ASV_4688   0   0   1   0   1   3   2   1   0   0   0   0   0   0   0   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4605   0   0   0   0   0   2   0   1   0   0  12   0   0   0   0   0
## ASV_5222   0   0   2   1   2   0   0   1   1   0   0   0   0   0   0   1
## ASV_5594   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3987   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_2401   0   0   1   4   0   0   0   0   0   0   0   0   1   0   0   1
## ASV_4992   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_1856   0   0   1   0   2   0   0   0   0   0   2   0   0   0   0   0
## ASV_3262   0   0   1   0   1   1   0   0   0   0   0   0   0   1   0   0
## ASV_5025   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4353   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4378   0   1   0   0   1   0   0   0   1   0   0   0   0   0   0   0
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3201   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_2076   0   0   0   0   3   1   0   0   0   0   0   0   0   0   0   0
## ASV_3120   0   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_2445   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1307   0   2   0   0   0   1   0   0   1   0   0   0   0   0   0   0
## ASV_5210   1   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2550   2   0   0   0   0   2   1   0   0   0   0   0   0   0   0   0
## ASV_4422   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3119   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5444   0   2   0   0   0   0   0   1   0   0   0   0   1   0   0   1
## ASV_2687   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4612   0   0   0   0   0   0   0   0   1   0   0   0   0   0   1   0
## ASV_5614   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1213   0   0   0   0   0   0   0   0   0   0   0   1   1   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5595   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4629   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3905   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5108   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5036   1   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5269   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4849   1   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_3829   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1688   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4267   0   3   1   1   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_4142   0   0   0   0   0   1   0   0   1   0   0   0   0   0   0   0
## ASV_4771   1   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3902   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_893    0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_1679   1   2   0   0   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_4340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##          298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_5569   0   0   0   0   0   0   3   0   0   0   0   0   0   0   0   0
## ASV_204    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4099   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_878    3   0   0   0   4   6   2   4   2   2   2   0   3   0   2   4
## ASV_5218   0   0   0   1   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_724    0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5230   0   0   0   0   0   0   0   0   0   0   0   3   0   0   0   0
## ASV_5009   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2417   0   0   0   0   1   0   1   2   2   3   2   2   2   0   1   1
## ASV_2322   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_113    0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5397   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4951   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5246   0   0   0   0   0   0   0   0   0   0   0   0   1   0   1   0
## ASV_4383   1   0   0   0   0   1   0   0   0   0   1   1   1   0   0   0
## ASV_5288   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_1258   4   2   0   1   2   1   5   0   1   2   2   0   0   0   2   4
## ASV_5496   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4673   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_4670   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4857   0   0   0   0   0   0   0   0   0   0   2   0   0   0   0   0
## ASV_5547   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4998   0   0   0   0   0   0   0   0   0   0   0   0   3   0   0   0
## ASV_4508   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2399   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_5206   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   0   0   0   0   0   0   0   0   2   0   1   0   0   1   0   2
## ASV_1078   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_2658   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   1
## ASV_2389   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_1853   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_4912   0   0   0   0   0   0   0   0   0   0   1   1   0   0   0   0
## ASV_5382   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2915   0   0   0   0   0   0   0   1   0   0   0   1   1   0   1   0
## ASV_4015   0   0   0   0   0   0   0   0   0   0   0   0   1   0   1   1
## ASV_4126   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4688   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4605   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5222   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5594   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_3987   1   0   0   0   0   0   0   0   0   0   0   1   6   0   0   0
## ASV_5262   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_2401   0   0   0   0   0   0   0   0   0   0   0   5   0   2   0   0
## ASV_4992   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1856   1   0   0   1   0   0   0   2   0   0   0   0   0   0   0   0
## ASV_3262   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   1
## ASV_5025   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4353   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4378   0   0   0   0   0   0   0   0   0   1   0   1   0   0   0   0
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3201   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2076   0   0   0   0   0   0   0   3   0   0   0   0   0   0   0   1
## ASV_3120   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2445   0   0   0   0   0   0   0   0   0   1   0   0   1   0   0   0
## ASV_1307   0   0   0   0   1   0   0   1   0   0   0   1   1   0   0   0
## ASV_5210   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2550   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4422   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_3119   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
## ASV_5444   0   1   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_2687   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_4612   1   0   0   0   0   0   0   0   0   1   1   0   0   0   0   0
## ASV_5614   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1213   0   0   0   0   0   1   0   0   0   0   2   0   1   0   0   3
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5595   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_4629   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3905   0   0   1   0   0   1   0   0   0   0   0   0   0   1   0   0
## ASV_5108   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5036   0   1   0   0   2   0   0   0   0   1   0   0   0   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5269   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4849   0   0   0   0   0   0   1   1   0   0   0   0   0   0   0   0
## ASV_3829   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1688   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4267   0   0   1   0   1   0   0   0   0   0   0   0   0   0   1   0
## ASV_4142   0   0   0   0   0   0   0   0   1   0   0   1   1   0   0   0
## ASV_4771   0   1   0   0   0   0   1   0   0   0   0   0   0   0   0   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3902   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_893    0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_1679   0   0   0   0   0   0   0  11   5   9   3   3   9   0   0   3
## ASV_4340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##          360 361 362 363 365 379 380 381 382 383 384 385 386 387 388 389
## ASV_5569   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_204    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4099   0   0   0   1   0   0   0   0   0   0   0   0   1   0   0   3
## ASV_878    1   4   0   0   0   6  10   2   0   2   5   0   0   0   2   8
## ASV_5218   1   1   0   0   0   0   0   0   0   0   0   0   0   1   0   2
## ASV_724    0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_5230   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5009   0   0   1   0   0   0   0   0   0   0   3   0   0   0   0   0
## ASV_2417   1   0   0   0   2   0   0   0   1   0   0   0   0   0   0   0
## ASV_2322   1   0   1   0   0   0   0   0   0   0   1   1   0   0   0   0
## ASV_113    0   1   0   0   0   1   0   0   0   0   1   0   0   0   1   0
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5397   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4951   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5246   0   1   0   0   0   0   0   0   2   1   0   0   0   0   0   0
## ASV_4383   1   1   0   0   0   0   0   0   2   0   1   1   0   0   0   1
## ASV_5288   1   0   0   0   0   0   0   0   1   0   1   0   0   0   0   0
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_1258   1   4   4   2   1   1   2   7   6   1   2   3   2   1   5   1
## ASV_5496   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   1
## ASV_4673   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_4670   0   0   0   0   0   0   0   1   1   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   2   0   0   0   1   0   0   0   0
## ASV_4857   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5547   0   3   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_4998   0   2   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4508   1   0   1   0   0   0   0   0   0   0   4   0   0   0   1   1
## ASV_2399   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5206   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1078   0   4   0   0   0   0   1   0   0   0   0   0   1   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2658   0   1   0   0   0   0   0   1   0   1   0   0   0   0   0   1
## ASV_2389   2   0   0   1   0   0   1   0   1   0   0   1   0   0   0   0
## ASV_1853   0   1   0   0   0   0   0   0   0   1   0   0   0   0   0   1
## ASV_4912   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5382   2   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2915   1   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_4015   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4126   4   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_4688   0   0   2   0   0   0   0   0   0   0   0   0   1   2   0   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4605   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5222   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5594   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_3987   0   6   0   0   0   0   0   0   0   0  11   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2401   7   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4992   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_1856   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
## ASV_3262   0   0   0   0   0   1   0   0   3   1   1   0   0   0   0   0
## ASV_5025   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4353   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4378   1   0   0   0   1   0   0   0   2   0   0   0   3   0   0   1
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3201   0   0   0   0   0   0   0   0   1   0   2   0   0   0   0   0
## ASV_2076   0   0   1   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_3120   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_2445   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_1307   0   0   0   0   0   2   0   0   0   0   0   0   0   0   0   0
## ASV_5210   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2550   1   0   0   0   0   0   0   0   0   0   0   0   1   0   1   0
## ASV_4422   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3119   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5444   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2687   0   0   0   0   0   0   0   1   0   0   0   0   1   0   0   0
## ASV_4612   0   0   0   0   0   1   0   1   2   2   0   1   2   0   1   0
## ASV_5614   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1213   1   0   1   0   0   0   0   0   1   0   0   0   1   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5595   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4629   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_3905   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_5108   1   0   0   0   0   0   1   0   0   0   0   0   0   0   1   0
## ASV_5036   0   0   0   0   0   2   0   0   0   0   1   1   1   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_5269   0   3   0   0   0   0   0   0   1   0   4   0   0   0   0   0
## ASV_4849   0   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_3829   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_1688   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4267   0   1   0   0   1   3   1   0   1   0   0   0   3   1   1   0
## ASV_4142   0   0   0   0   0   0   1   0   2   0   0   0   1   0   0   1
## ASV_4771   0   0   1   0   0   0   0   0   0   0   0   0   3   0   1   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3902   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_893    0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_1679   8   2   2   2   4   0   0   0   0   0   0   0   0   0   0   0
## ASV_4340   0   0   0   0   0   0   0   0   0   0   2   0   0   0   1   0
##          390 505 506 507 508 509 510 511
## ASV_5569   0   0   0   0   0   0   0   0
## ASV_204    0   0   0   0   0   1   0   0
## ASV_4099   0   0   0   1   0   0   0   0
## ASV_878    0   0   0   3   0   6   6   7
## ASV_5218   0   0   0   0   0   0   1   0
## ASV_724    0   0   0   0   0   1   1   0
## ASV_5230   0   0   1   0   0   1   0   0
## ASV_5009   0   0   0   0   0   0   0   0
## ASV_2417   0   0   0   2   0   8   1   3
## ASV_2322   0   0   0   0   0   2   0   0
## ASV_113    0   0   1   0   0   0   0   0
## ASV_147    0   0   0   0   0   0   1   0
## ASV_5397   0   0   0   0   0   0   0   0
## ASV_4951   0   0   0   0   0   0   0   0
## ASV_5246   0   0   0   0   1   0   0   0
## ASV_4383   0   0   0   0   0   2   0   1
## ASV_5288   0   0   0   0   0   0   0   0
## ASV_5123   0   0   0   0   0   1   0   0
## ASV_5340   0   0   0   0   0   3   1   0
## ASV_1258   2   0   2   0   0   4   0   1
## ASV_5496   0   0   0   0   0   0   0   0
## ASV_4673   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   2   1   0
## ASV_4670   0   0   0   0   1   0   0   0
## ASV_5204   0   0   0   0   0   1   1   0
## ASV_4857   0   0   0   0   0   0   0   0
## ASV_5547   0   0   0   0   0   0   0   0
## ASV_4998   0   0   0   0   0   1   0   0
## ASV_4508   0   0   0   0   1   2   0   0
## ASV_2399   0   0   0   0   0   0   1   0
## ASV_5206   0   0   0   0   0   1   0   0
## ASV_1728   0   0   0   0   0   1   0   0
## ASV_1078   0   0   0   0   0   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0
## ASV_2658   0   0   0   0   0   0   1   0
## ASV_2389   0   0   0   0   0   1   0   0
## ASV_1853   0   1   0   0   0   0   1   0
## ASV_4912   0   0   0   0   0   0   0   0
## ASV_5382   0   0   0   0   0   2   0   0
## ASV_2915   0   0   0   0   0   0   0   0
## ASV_4015   0   0   1   0   0   0   0   0
## ASV_4126   0   0   0   0   1   0   0   1
## ASV_4688   0   0   1   0   0   0   0   0
## ASV_4324   0   0   0   0   0   1   0   0
## ASV_4605   0   0   0   0   1   0   0   0
## ASV_5222   0   0   0   0   0   0   0   0
## ASV_5594   0   0   0   0   0   0   0   0
## ASV_3987   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0
## ASV_2401   0   1   0   0   0   1   0   0
## ASV_4992   0   0   1   0   0   0   0   0
## ASV_1856   2   0   0   0   1   1   0   0
## ASV_3262   0   0   1   0   0   0   0   0
## ASV_5025   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   1   0   0   1
## ASV_4913   0   0   0   0   0   1   0   2
## ASV_3684   0   0   0   0   0   0   1   0
## ASV_4353   0   0   0   0   0   0   0   1
## ASV_4378   0   0   0   0   0   2   0   1
## ASV_1247   0   0   0   0   0   0   2   0
## ASV_3201   0   0   0   0   0   0   0   0
## ASV_2076   0   0   0   0   0   0   0   0
## ASV_3120   0   0   0   0   0   0   0   2
## ASV_2445   0   0   0   0   0   0   0   0
## ASV_1307   0   0   0   0   0   0   0   0
## ASV_5210   0   0   0   0   0   0   0   0
## ASV_2550   0   0   2   0   0   1   1   0
## ASV_4422   0   0   0   0   0   1   0   2
## ASV_3119   0   0   1   0   0   1   0   0
## ASV_5444   0   0   0   1   0   0   0   0
## ASV_2687   0   0   0   0   0   0   2   2
## ASV_4612   0   1   0   0   0   0   0   0
## ASV_5614   0   0   0   0   0   2   0   0
## ASV_1213   0   0   1   0   0   1   0   0
## ASV_5192   0   0   0   0   0   0   0   0
## ASV_5595   0   0   0   0   0   0   0   0
## ASV_4629   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   1
## ASV_5568   0   0   0   0   0   0   1   0
## ASV_3905   0   0   0   0   0   0   2   0
## ASV_5108   0   0   0   0   0   0   0   0
## ASV_5036   0   0   0   0   0   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0
## ASV_5269   0   0   0   0   0   0   0   0
## ASV_4849   0   0   0   0   0   1   0   0
## ASV_3829   0   0   0   0   0   0   0   0
## ASV_1688   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   1   0
## ASV_4267   0   0   0   0   0   0   0   0
## ASV_4142   1   0   0   1   1   1   1   2
## ASV_4771   0   0   0   0   0   3   1   0
## ASV_5492   0   0   1   0   0   0   0   0
## ASV_3902   0   0   0   0   0   1   0   0
## ASV_4822   0   1   0   0   0   0   0   0
## ASV_893    0   0   0   1   0   3   1   0
## ASV_1679   0   1   4   2   1  11   4  17
## ASV_4340   0   0   0   0   0   0   0   0

Yikes, 99 taxa could not be fit with the model, but this looks to be due to circumstances where there is very few reads for a particular ASV (thus, a model can’t be fit) or instances where there is only reads in one sample type.

Now, we will return to the corncob output. We can see a list of differentially-abundant taxa using:

##   [1] "Firmicutes_Lachnospiraceae_Lachnospiraceae_FE2018_group"              
##   [2] "Firmicutes_Lachnospiraceae_Lachnospiraceae_ND3007_group"              
##   [3] "Firmicutes_Lachnospiraceae_Lachnospiraceae_NK4A136_group"             
##   [4] "Firmicutes_Lachnospiraceae_Acetatifactor"                             
##   [5] "Firmicutes_Lachnospiraceae_Howardella"                                
##   [6] "Firmicutes_Lachnospiraceae_Marvinbryantia"                            
##   [7] "Firmicutes_Lachnospiraceae_Blautia"                                   
##   [8] "Firmicutes_Lachnospiraceae_Lachnospiraceae_NK3A20_group"              
##   [9] "Firmicutes_Lachnospiraceae_XBB1006"                                   
##  [10] "Firmicutes_Lachnospiraceae_Roseburia"                                 
##  [11] "Firmicutes_Lachnospiraceae_Shuttleworthia"                            
##  [12] "Firmicutes_Lachnospiraceae_Pseudobutyrivibrio"                        
##  [13] "Firmicutes_Lachnospiraceae_Lachnospiraceae_AC2044_group"              
##  [14] "Firmicutes_Lachnospiraceae_Moryella"                                  
##  [15] "Firmicutes_Lachnospiraceae_Butyrivibrio_2"                            
##  [16] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-002"                   
##  [17] "Firmicutes_Lachnospiraceae_Acetitomaculum"                            
##  [18] "Firmicutes_Lachnospiraceae_Lachnoclostridium_10"                      
##  [19] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-006"                   
##  [20] "Firmicutes_Lachnospiraceae_Coprococcus_2"                             
##  [21] "Firmicutes_Defluviitaleaceae_Defluviitaleaceae_UCG-011"               
##  [22] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-010"                   
##  [23] "Firmicutes_Lachnospiraceae_Coprococcus_1"                             
##  [24] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-008"                   
##  [25] "Firmicutes_Lachnospiraceae_Lachnospiraceae_FCS020_group"              
##  [26] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-009"                   
##  [27] "Firmicutes_Lachnospiraceae_Tyzzerella_3"                              
##  [28] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-014"                   
##  [29] "Firmicutes_Veillonellaceae_Veillonellaceae_UCG-001"                   
##  [30] "Firmicutes_Veillonellaceae_Quinella"                                  
##  [31] "Firmicutes_Veillonellaceae_Selenomonas_1"                             
##  [32] "Firmicutes_Veillonellaceae_Schwartzia"                                
##  [33] "Firmicutes_Veillonellaceae_Selenomonas_4"                             
##  [34] "Firmicutes_Veillonellaceae_Anaerovibrio"                              
##  [35] "Firmicutes_Family_XIII_Mogibacterium"                                 
##  [36] "Firmicutes_Family_XIII_Family_XIII_AD3011_group"                      
##  [37] "Firmicutes_Family_XIII_Family_XIII_UCG-001"                           
##  [38] "Firmicutes_Family_XIII_Anaerovorax"                                   
##  [39] "Tenericutes_Anaeroplasmataceae_Anaeroplasma"                          
##  [40] "Firmicutes_Erysipelotrichaceae_Catenisphaera"                         
##  [41] "Firmicutes_Erysipelotrichaceae_Solobacterium"                         
##  [42] "Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009"           
##  [43] "Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004"           
##  [44] "Firmicutes_Streptococcaceae_Streptococcus"                            
##  [45] "Firmicutes_Lactobacillaceae_Lactobacillus"                            
##  [46] "Firmicutes_Staphylococcaceae_Staphylococcus"                          
##  [47] "Firmicutes_Planococcaceae_Planococcus"                                
##  [48] "Firmicutes_Clostridiaceae_1_Clostridium_sensu_stricto_1"              
##  [49] "Firmicutes_Acidaminococcaceae_Succiniclasticum"                       
##  [50] "Firmicutes_Syntrophomonadaceae_Pelospora"                             
##  [51] "Firmicutes_Eubacteriaceae_Anaerofustis"                               
##  [52] "Elusimicrobia_Elusimicrobiaceae_Elusimicrobium"                       
##  [53] "Proteobacteria_Pseudomonadaceae_Pseudomonas"                          
##  [54] "Proteobacteria_Succinivibrionaceae_Succinimonas"                      
##  [55] "Proteobacteria_Succinivibrionaceae_Anaerobiospirillum"                
##  [56] "Proteobacteria_Succinivibrionaceae_Succinivibrio"                     
##  [57] "Proteobacteria_Burkholderiaceae_Sutterella"                           
##  [58] "Proteobacteria_Burkholderiaceae_Variovorax"                           
##  [59] "Proteobacteria_Burkholderiaceae_Massilia"                             
##  [60] "Proteobacteria_Cardiobacteriaceae_Suttonella"                         
##  [61] "Proteobacteria_Succinivibrionaceae_Ruminobacter"                      
##  [62] "Proteobacteria_Succinivibrionaceae_Succinivibrionaceae_UCG-002"       
##  [63] "Proteobacteria_Desulfobulbaceae_Desulfobulbus"                        
##  [64] "Fusobacteria_Fusobacteriaceae_Fusobacterium"                          
##  [65] "Euryarchaeota_Methanobacteriaceae_Methanosphaera"                     
##  [66] "Euryarchaeota_Methanomethylophilaceae_Candidatus_Methanomethylophilus"
##  [67] "Proteobacteria_Desulfovibrionaceae_Desulfovibrio"                     
##  [68] "Proteobacteria_Desulfovibrionaceae_Mailhella"                         
##  [69] "Proteobacteria_Desulfuromonadaceae_Desulfuromonas"                    
##  [70] "Spirochaetes_Spirochaetaceae_M2PT2-76_termite_group"                  
##  [71] "Actinobacteria_Corynebacteriaceae_Corynebacterium"                    
##  [72] "Actinobacteria_Nocardiaceae_Rhodococcus"                              
##  [73] "Actinobacteria_Coriobacteriales_Incertae_Sedis_Raoultibacter"         
##  [74] "Actinobacteria_Eggerthellaceae_DNF00809"                              
##  [75] "Actinobacteria_Atopobiaceae_Olsenella"                                
##  [76] "Actinobacteria_Atopobiaceae_Atopobium"                                
##  [77] "Fibrobacteres_Fibrobacteraceae_Fibrobacter"                           
##  [78] "Chloroflexi_Anaerolineaceae_Flexilinea"                               
##  [79] "Synergistetes_Synergistaceae_Pyramidobacter"                          
##  [80] "Firmicutes_Christensenellaceae_Christensenellaceae_R-7_group"         
##  [81] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-010"                   
##  [82] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-003"                  
##  [83] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-004"                  
##  [84] "Bacteroidetes_Prevotellaceae_Prevotellaceae_Ga6A1_group"              
##  [85] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-001"                  
##  [86] "Bacteroidetes_Prevotellaceae_Prevotella_1"                            
##  [87] "Bacteroidetes_Prevotellaceae_Prevotellaceae_NK3B31_group"             
##  [88] "Bacteroidetes_Prevotellaceae_Prevotellaceae_YAB2003_group"            
##  [89] "Bacteroidetes_Rikenellaceae_Rikenellaceae_RC9_gut_group"              
##  [90] "Bacteroidetes_Rikenellaceae_U29-B03"                                  
##  [91] "Bacteroidetes_Porphyromonadaceae_Porphyromonas"                       
##  [92] "Firmicutes_Ruminococcaceae_Ruminiclostridium_6"                       
##  [93] "Firmicutes_Ruminococcaceae_Ruminococcus_1"                            
##  [94] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-001"                   
##  [95] "Firmicutes_Ruminococcaceae_Ruminococcus_2"                            
##  [96] "Firmicutes_Ruminococcaceae_CAG-352"                                   
##  [97] "Firmicutes_Ruminococcaceae_Saccharofermentans"                        
##  [98] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-013"                   
##  [99] "Firmicutes_Ruminococcaceae_Ruminococcaceae_NK4A214_group"             
## [100] "Firmicutes_Ruminococcaceae_Papillibacter"                             
## [101] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-005"                   
## [102] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-002"                   
## [103] "Firmicutes_Ruminococcaceae_Ruminiclostridium_9"                       
## [104] "Firmicutes_Ruminococcaceae_Ruminococcaceae_V9D2013_group"             
## [105] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-004"                   
## [106] "Firmicutes_Lachnospiraceae_Lachnospiraceae_XPB1014_group"             
## [107] "Firmicutes_Lachnospiraceae_possible_genus_Sk018"                      
## [108] "Firmicutes_Lachnospiraceae_probable_genus_10"

There are 108 genera differentially abundant. We will look at the unique families they represent.

# of significant genera in each family
Var1	Freq
Firmicutes_Lachnospiraceae	29
Firmicutes_Ruminococcaceae	16
Bacteroidetes_Prevotellaceae	7
Firmicutes_Veillonellaceae	6
Proteobacteria_Succinivibrionaceae	5
Firmicutes_Erysipelotrichaceae	4
Firmicutes_Family_XIII	4
Proteobacteria_Burkholderiaceae	3
Actinobacteria_Atopobiaceae	2
Bacteroidetes_Rikenellaceae	2
Proteobacteria_Desulfovibrionaceae	2
Actinobacteria_Coriobacteriales_Incertae_Sedis	1
Actinobacteria_Corynebacteriaceae	1
Actinobacteria_Eggerthellaceae	1
Actinobacteria_Nocardiaceae	1
Bacteroidetes_Porphyromonadaceae	1
Chloroflexi_Anaerolineaceae	1
Elusimicrobia_Elusimicrobiaceae	1
Euryarchaeota_Methanobacteriaceae	1
Euryarchaeota_Methanomethylophilaceae	1
Fibrobacteres_Fibrobacteraceae	1
Firmicutes_Acidaminococcaceae	1
Firmicutes_Christensenellaceae	1
Firmicutes_Clostridiaceae_1	1
Firmicutes_Defluviitaleaceae	1
Firmicutes_Eubacteriaceae	1
Firmicutes_Lactobacillaceae	1
Firmicutes_Planococcaceae	1
Firmicutes_Staphylococcaceae	1
Firmicutes_Streptococcaceae	1
Firmicutes_Syntrophomonadaceae	1
Fusobacteria_Fusobacteriaceae	1
Proteobacteria_Cardiobacteriaceae	1
Proteobacteria_Desulfobulbaceae	1
Proteobacteria_Desulfuromonadaceae	1
Proteobacteria_Pseudomonadaceae	1
Spirochaetes_Spirochaetaceae	1
Synergistetes_Synergistaceae	1
Tenericutes_Anaeroplasmataceae	1

From this we can see that Lachnospiraceae, Ruminococcaceae, and Prevotellaceae were the most common families to be differentially abundant in grab samples vs other rumen sample types. We will take a closer look at all ASVs differentially abundant.

Differentially Abundant Taxa
	p_value	ASV	Taxa
1	2.43e-03	ASV_1	Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group
2	2.43e-03	ASV_10	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans
3	2.43e-03	ASV_1016	Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis
4	2.43e-03	ASV_103	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1
5	2.43e-03	ASV_105	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group
6	2.43e-03	ASV_1130	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018
7	2.43e-03	ASV_1132	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group
8	2.43e-03	ASV_1161	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006
9	2.43e-03	ASV_117	Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus
10	2.43e-03	ASV_120	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002
11	2.43e-03	ASV_124	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group
12	2.43e-03	ASV_1366	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio
13	2.43e-03	ASV_1372	Bacteria_Fusobacteria_Fusobacteriia_Fusobacteriales_Fusobacteriaceae_Fusobacterium
15	2.43e-03	ASV_14	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium
16	2.43e-03	ASV_1403	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Howardella
17	2.43e-03	ASV_141	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrio
18	2.43e-03	ASV_145	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group
21	2.43e-03	ASV_154	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004
25	2.43e-03	ASV_172	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809
26	2.43e-03	ASV_176	Bacteria_Proteobacteria_Gammaproteobacteria_Pseudomonadales_Pseudomonadaceae_Pseudomonas
27	2.43e-03	ASV_183	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014
29	2.43e-03	ASV_192	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group
30	2.43e-03	ASV_2	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group
31	2.43e-03	ASV_20	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1
32	2.43e-03	ASV_201	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group
33	2.43e-03	ASV_210	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10
39	2.43e-03	ASV_2183	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_3
40	2.43e-03	ASV_22	Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella
41	2.43e-03	ASV_2244	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Schwartzia
42	2.43e-03	ASV_23	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1
44	2.43e-03	ASV_235	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1
45	2.43e-03	ASV_2419	Bacteria_Proteobacteria_Gammaproteobacteria_Cardiobacteriales_Cardiobacteriaceae_Suttonella
46	2.43e-03	ASV_246	Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma
47	2.43e-03	ASV_248	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group
48	2.43e-03	ASV_25	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio
49	2.43e-03	ASV_2517	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Quinella
51	2.43e-03	ASV_298	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax
53	2.43e-03	ASV_305	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013
54	2.43e-03	ASV_311	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella
57	2.43e-03	ASV_320	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10
60	2.43e-03	ASV_348	Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011
61	2.43e-03	ASV_357	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002
62	2.43e-03	ASV_37	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter
63	2.43e-03	ASV_376	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group
65	2.43e-03	ASV_399	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_2
66	2.43e-03	ASV_4	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group
68	2.43e-03	ASV_418	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium
71	2.43e-03	ASV_428	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia
72	2.43e-03	ASV_429	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetatifactor
73	2.43e-03	ASV_439	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella
75	2.43e-03	ASV_450	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter
77	2.43e-03	ASV_457	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008
78	2.43e-03	ASV_462	Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium
80	2.43e-03	ASV_471	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium
81	2.43e-03	ASV_474	Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001
82	2.43e-03	ASV_499	Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Pyramidobacter
83	2.43e-03	ASV_511	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinimonas
84	2.43e-03	ASV_520	Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus
86	2.43e-03	ASV_57	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia
88	2.43e-03	ASV_636	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
89	2.43e-03	ASV_656	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter
90	2.43e-03	ASV_66	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum
92	2.43e-03	ASV_670	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Roseburia
94	2.43e-03	ASV_68	Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter
95	2.43e-03	ASV_71	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2
96	2.43e-03	ASV_72	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001
97	2.43e-03	ASV_733	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
98	2.43e-03	ASV_793	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-006
99	2.43e-03	ASV_8	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum
100	2.43e-03	ASV_83	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_9
102	2.43e-03	ASV_90	Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella
104	2.43e-03	ASV_902	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002
105	2.43e-03	ASV_91	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003
108	2.43e-03	ASV_970	Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Anaerobiospirillum
22	4.59e-03	ASV_16	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group
23	4.59e-03	ASV_1658	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_U29-B03
28	4.59e-03	ASV_184	Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera
70	4.59e-03	ASV_4270	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Porphyromonadaceae_Porphyromonas
38	6.56e-03	ASV_2174	Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Variovorax
56	6.56e-03	ASV_3188	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_CAG-352
93	6.56e-03	ASV_674	Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera
101	6.56e-03	ASV_887	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK4A136_group
34	8.25e-03	ASV_212	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010
74	8.25e-03	ASV_44	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005
103	8.25e-03	ASV_901	Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_M2PT2-76_termite_group
106	8.25e-03	ASV_921	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-010
107	8.25e-03	ASV_953	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group
43	1.01e-02	ASV_2300	Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1
67	1.01e-02	ASV_409	Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea
19	1.16e-02	ASV_149	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio
50	1.16e-02	ASV_2617	Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_YAB2003_group
55	1.16e-02	ASV_3129	Bacteria_Firmicutes_Clostridia_Clostridiales_Syntrophomonadaceae_Pelospora
64	1.16e-02	ASV_3936	Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae_Candidatus_Methanomethylophilus
14	1.70e-02	ASV_1389	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfuromonadales_Desulfuromonadaceae_Desulfuromonas
24	1.70e-02	ASV_169	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-004
58	2.38e-02	ASV_3273	Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium
76	2.38e-02	ASV_456	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Veillonellaceae_UCG-001
91	2.38e-02	ASV_669	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Shuttleworthia
37	2.53e-02	ASV_2171	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-001
36	2.88e-02	ASV_2134	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_2
79	3.19e-02	ASV_4697	Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_4
52	4.40e-02	ASV_2981	Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae_Planococcus
20	4.52e-02	ASV_1509	Bacteria_Firmicutes_Bacilli_Lactobacillales_Lactobacillaceae_Lactobacillus
35	4.52e-02	ASV_2130	Bacteria_Proteobacteria_Deltaproteobacteria_Desulfobacterales_Desulfobulbaceae_Desulfobulbus
59	4.52e-02	ASV_3393	Bacteria_Firmicutes_Bacilli_Bacillales_Staphylococcaceae_Staphylococcus
69	4.52e-02	ASV_423	Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Massilia
87	4.52e-02	ASV_601	Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009
85	4.64e-02	ASV_560	Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6

Taking a closer look at the break down of Fibrobacteraceae

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##        Kingdom    Phylum          Class           Order            
## ASV_68 "Bacteria" "Fibrobacteres" "Fibrobacteria" "Fibrobacterales"
##        Family             Genus Species
## ASV_68 "Fibrobacteraceae" NA    NA

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -3.80549    0.13890 -27.397
## Sample_TypeStomach Tube      -1.75544    0.21039  -8.344
## Sample_TypeLiquid Strained   -0.13258    0.12873  -1.030
## Sample_TypeSolid             -0.44736    0.13872  -3.225
## Sample_TypeLiquid Unstrained -0.91152    0.18408  -4.952
## CowIDCow_2477                 0.19984    0.13799   1.448
## CowIDCow_2549                 0.04026    0.14421   0.279
## CowIDCow_796                 -0.07145    0.14797  -0.483
## DayDay_7                     -0.10136    0.13020  -0.778
## DayDay_9                      0.11523    0.11857   0.972
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube             0.00000000011 ***
## Sample_TypeLiquid Strained                0.30854    
## Sample_TypeSolid                          0.00235 ** 
## Sample_TypeLiquid Unstrained        0.00001080133 ***
## CowIDCow_2477                             0.15447    
## CowIDCow_2549                             0.78139    
## CowIDCow_796                              0.63152    
## DayDay_7                                  0.44037    
## DayDay_9                                  0.33635    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.2354     0.2076  -30.03 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -272.44

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -3.64488    0.14105 -25.841
## Sample_TypeStomach Tube      -1.77488    0.21439  -8.279
## Sample_TypeLiquid Strained   -0.10065    0.13002  -0.774
## Sample_TypeSolid             -0.44883    0.14104  -3.182
## Sample_TypeLiquid Unstrained -0.89898    0.18617  -4.829
## CowIDCow_2477                 0.20392    0.13940   1.463
## CowIDCow_2549                 0.03105    0.14606   0.213
## CowIDCow_796                 -0.07921    0.14981  -0.529
## DayDay_7                     -0.09707    0.13200  -0.735
## DayDay_9                      0.12889    0.12009   1.073
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube            0.000000000136 ***
## Sample_TypeLiquid Strained                0.44289    
## Sample_TypeSolid                          0.00265 ** 
## Sample_TypeLiquid Unstrained       0.000016227326 ***
## CowIDCow_2477                             0.15045    
## CowIDCow_2549                             0.83262    
## CowIDCow_796                              0.59961    
## DayDay_7                                  0.46593    
## DayDay_9                                  0.28886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0413     0.2073  -29.14 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -272.61

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##         Kingdom    Phylum       Class        Order          
## ASV_103 "Bacteria" "Firmicutes" "Clostridia" "Clostridiales"
##         Family            Genus            Species
## ASV_103 "Ruminococcaceae" "Ruminococcus_1" NA

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                  -3.200533   0.079867 -40.073
## Sample_TypeStomach Tube      -0.767638   0.092303  -8.316
## Sample_TypeLiquid Strained   -0.424786   0.082959  -5.120
## Sample_TypeSolid              0.004558   0.073561   0.062
## Sample_TypeLiquid Unstrained -0.493629   0.094815  -5.206
## CowIDCow_2477                -0.129281   0.079632  -1.623
## CowIDCow_2549                 0.066452   0.076700   0.866
## CowIDCow_796                  0.007782   0.077747   0.100
## DayDay_7                     -0.282765   0.071308  -3.965
## DayDay_9                     -0.111542   0.063832  -1.747
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube             0.00000000012 ***
## Sample_TypeLiquid Strained          0.00000615317 ***
## Sample_TypeSolid                          0.95087    
## Sample_TypeLiquid Unstrained        0.00000461602 ***
## CowIDCow_2477                             0.11147    
## CowIDCow_2549                             0.39088    
## CowIDCow_796                              0.92072    
## DayDay_7                                  0.00026 ***
## DayDay_9                                  0.08738 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.0052     0.2308  -30.36 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -268.16

Pulling out the model for Fibrobacteraceae

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##        Kingdom    Phylum          Class           Order            
## ASV_68 "Bacteria" "Fibrobacteres" "Fibrobacteria" "Fibrobacterales"
##        Family             Genus         Species
## ASV_68 "Fibrobacteraceae" "Fibrobacter" NA

## [1] "Model for Fibrobacter"

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -3.64488    0.14105 -25.841
## Sample_TypeStomach Tube      -1.77488    0.21439  -8.279
## Sample_TypeLiquid Strained   -0.10065    0.13002  -0.774
## Sample_TypeSolid             -0.44883    0.14104  -3.182
## Sample_TypeLiquid Unstrained -0.89898    0.18617  -4.829
## CowIDCow_2477                 0.20392    0.13940   1.463
## CowIDCow_2549                 0.03105    0.14606   0.213
## CowIDCow_796                 -0.07921    0.14981  -0.529
## DayDay_7                     -0.09707    0.13200  -0.735
## DayDay_9                      0.12889    0.12009   1.073
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube            0.000000000136 ***
## Sample_TypeLiquid Strained                0.44289    
## Sample_TypeSolid                          0.00265 ** 
## Sample_TypeLiquid Unstrained       0.000016227326 ***
## CowIDCow_2477                             0.15045    
## CowIDCow_2549                             0.83262    
## CowIDCow_796                              0.59961    
## DayDay_7                                  0.46593    
## DayDay_9                                  0.28886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0413     0.2073  -29.14 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -272.61

Graphing out all the families that are significantly different between grab samples and other rumen sample types.

Pulling out the model for genera in Prevotellaceae here.

## Taxonomy Table:     [7 taxa by 7 taxonomic ranks]:
##          Kingdom    Phylum          Class         Order          
## ASV_91   "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_154  "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_201  "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_72   "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_20   "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_1132 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_2617 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
##          Family           Genus                          Species
## ASV_91   "Prevotellaceae" "Prevotellaceae_UCG-003"       NA     
## ASV_154  "Prevotellaceae" "Prevotellaceae_UCG-004"       NA     
## ASV_201  "Prevotellaceae" "Prevotellaceae_Ga6A1_group"   NA     
## ASV_72   "Prevotellaceae" "Prevotellaceae_UCG-001"       NA     
## ASV_20   "Prevotellaceae" "Prevotella_1"                 NA     
## ASV_1132 "Prevotellaceae" "Prevotellaceae_NK3B31_group"  NA     
## ASV_2617 "Prevotellaceae" "Prevotellaceae_YAB2003_group" NA

## [1] "Model for Prevotella_1"

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -2.75424    0.11121 -24.766
## Sample_TypeStomach Tube       0.22141    0.11474   1.930
## Sample_TypeLiquid Strained    1.25445    0.10022  12.517
## Sample_TypeSolid              0.06410    0.11773   0.544
## Sample_TypeLiquid Unstrained  0.70775    0.11798   5.999
## CowIDCow_2477                 0.09219    0.09069   1.017
## CowIDCow_2549                 0.08058    0.09057   0.890
## CowIDCow_796                 -0.01757    0.09205  -0.191
## DayDay_7                      0.04570    0.08404   0.544
## DayDay_9                      0.11046    0.07559   1.461
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                     0.060 .  
## Sample_TypeLiquid Strained   0.000000000000000293 ***
## Sample_TypeSolid                            0.589    
## Sample_TypeLiquid Unstrained 0.000000313650803771 ***
## CowIDCow_2477                               0.315    
## CowIDCow_2549                               0.378    
## CowIDCow_796                                0.849    
## DayDay_7                                    0.589    
## DayDay_9                                    0.151    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -5.2565     0.1958  -26.84 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -347.35

## [1] "Model for Prevotellaceae_UCG-003"

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                  -4.269117   0.098473 -43.353
## Sample_TypeStomach Tube       0.367820   0.100674   3.654
## Sample_TypeLiquid Strained    1.162644   0.089297  13.020
## Sample_TypeSolid              0.007731   0.107603   0.072
## Sample_TypeLiquid Unstrained  0.885074   0.100617   8.796
## CowIDCow_2477                 0.046630   0.077879   0.599
## CowIDCow_2549                 0.162481   0.076833   2.115
## CowIDCow_796                  0.053311   0.078707   0.677
## DayDay_7                     -0.095193   0.072098  -1.320
## DayDay_9                      0.031053   0.062622   0.496
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                  0.000673 ***
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeSolid                         0.943044    
## Sample_TypeLiquid Unstrained      0.0000000000246 ***
## CowIDCow_2477                            0.552342    
## CowIDCow_2549                            0.040025 *  
## CowIDCow_796                             0.501657    
## DayDay_7                                 0.193406    
## DayDay_9                                 0.622390    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.0921     0.2334  -30.39 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -263.07

## [1] "Model for Prevotellaceae_UCG-004"

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.47683    0.13755 -39.816
## Sample_TypeStomach Tube      -0.09603    0.12682  -0.757
## Sample_TypeLiquid Strained   -0.69899    0.15142  -4.616
## Sample_TypeSolid              0.30414    0.11276   2.697
## Sample_TypeLiquid Unstrained -0.23747    0.14817  -1.603
## CowIDCow_2477                 0.10932    0.12497   0.875
## CowIDCow_2549                 0.38583    0.11905   3.241
## CowIDCow_796                  0.26012    0.12265   2.121
## DayDay_7                      0.04305    0.10408   0.414
## DayDay_9                      0.02275    0.09893   0.230
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                   0.45285    
## Sample_TypeLiquid Strained              0.0000326 ***
## Sample_TypeSolid                          0.00980 ** 
## Sample_TypeLiquid Unstrained              0.11600    
## CowIDCow_2477                             0.38634    
## CowIDCow_2549                             0.00224 ** 
## CowIDCow_796                              0.03948 *  
## DayDay_7                                  0.68109    
## DayDay_9                                  0.81918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -8.1820     0.3045  -26.87 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -194.82

## [1] "Model for Prevotellaceae_UCG-001"

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -4.48384    0.09140 -49.060
## Sample_TypeStomach Tube      -0.04059    0.09828  -0.413
## Sample_TypeLiquid Strained    0.84341    0.08280  10.186
## Sample_TypeSolid              0.01873    0.09440   0.198
## Sample_TypeLiquid Unstrained  0.45009    0.09672   4.654
## CowIDCow_2477                -0.12107    0.07433  -1.629
## CowIDCow_2549                -0.12110    0.07549  -1.604
## CowIDCow_796                 -0.16120    0.07646  -2.108
## DayDay_7                      0.01508    0.07125   0.212
## DayDay_9                      0.18122    0.06336   2.860
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.6816    
## Sample_TypeLiquid Strained      0.000000000000291 ***
## Sample_TypeSolid                           0.8436    
## Sample_TypeLiquid Unstrained    0.000028859046887 ***
## CowIDCow_2477                              0.1103    
## CowIDCow_2549                              0.1157    
## CowIDCow_796                               0.0406 *  
## DayDay_7                                   0.8333    
## DayDay_9                                   0.0064 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.7963     0.2788  -27.96 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -235.28

## [1] "Model for Prevotellaceae_NK3B31_group"

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.87144    0.16744 -35.066
## Sample_TypeStomach Tube      -0.58858    0.19073  -3.086
## Sample_TypeLiquid Strained   -1.08143    0.22449  -4.817
## Sample_TypeSolid              0.25058    0.14697   1.705
## Sample_TypeLiquid Unstrained -0.53659    0.21017  -2.553
## CowIDCow_2477                -0.50695    0.16957  -2.990
## CowIDCow_2549                -0.21946    0.15718  -1.396
## CowIDCow_796                 -0.16570    0.15706  -1.055
## DayDay_7                     -0.09407    0.14453  -0.651
## DayDay_9                     -0.14163    0.13953  -1.015
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                   0.00347 ** 
## Sample_TypeLiquid Strained              0.0000169 ***
## Sample_TypeSolid                          0.09510 .  
## Sample_TypeLiquid Unstrained              0.01414 *  
## CowIDCow_2477                             0.00452 ** 
## CowIDCow_2549                             0.16948    
## CowIDCow_796                              0.29704    
## DayDay_7                                  0.51841    
## DayDay_9                                  0.31552    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)   -8.914      0.470  -18.97 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -151.98

Just looking at methanogens.

Pulling out the model for the ASVs here.

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##         Kingdom   Phylum          Class             Order               
## ASV_184 "Archaea" "Euryarchaeota" "Methanobacteria" "Methanobacteriales"
##         Family                Genus            Species
## ASV_184 "Methanobacteriaceae" "Methanosphaera" NA

## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.40980    0.18307 -29.551
## Sample_TypeStomach Tube       0.02828    0.17737   0.159
## Sample_TypeLiquid Strained   -0.89032    0.22933  -3.882
## Sample_TypeSolid              0.16642    0.17014   0.978
## Sample_TypeLiquid Unstrained -0.69890    0.25423  -2.749
## CowIDCow_2477                -0.46923    0.17347  -2.705
## CowIDCow_2549                -0.76002    0.19214  -3.956
## CowIDCow_796                 -0.11309    0.16185  -0.699
## DayDay_7                      0.05906    0.15644   0.378
## DayDay_9                     -0.02356    0.15212  -0.155
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                  0.874046    
## Sample_TypeLiquid Strained               0.000336 ***
## Sample_TypeSolid                         0.333253    
## Sample_TypeLiquid Unstrained             0.008573 ** 
## CowIDCow_2477                            0.009610 ** 
## CowIDCow_2549                            0.000268 ***
## CowIDCow_796                             0.488308    
## DayDay_7                                 0.707568    
## DayDay_9                                 0.877614    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.6642     0.2631  -29.13 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -185.92

Checking to see what samples Methanimicrococcus is found in.

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##          Kingdom   Phylum          Class             Order              
## ASV_5594 "Archaea" "Euryarchaeota" "Methanomicrobia" "Methanosarcinales"
##          Family               Genus                Species
## ASV_5594 "Methanosarcinaceae" "Methanimicrococcus" NA

## [1] Liquid Strained Solid          
## Levels: Liquid Strained Solid

## OTU Table:          [1 taxa and 2 samples]
##                      taxa are rows
##          309 389
## ASV_5594   1   1

Transfaunating what communites?

Based on the analysis above it would see that transfaunation by getting a stomach tube sample would be close to getting a full community into the sick cow. However, if you strain the sample you will bias the communities that your transfaunation gives.

Communites found in stomach tube samples

For this I can think we can just reference the phyla graphs in the “Abundance of Phyla” section. Also we will take a look more specifically at the taxa that the stomach tube samples have in common.

There are 4019 ASVs in Stomach tube samples, but only 255 taxa are present in all stomach tube samples. Due to the variability of stomach tube samples I suspect that with more sampls you will have reduce taxa in common. Stomach tube samples are composed of 20 phyla, 65 orders, 98 families and 236 genera.

Grab vs stomach tube samples

## NULL

## [1] "Families in grab samples not in stomach tube"

##  [1] "Sellimonas"         "Incertae_Sedis"     "Sarcina"           
##  [4] "Rhodobacter"        "Ketogulonicigenium" "Sphingobium"       
##  [7] "Sphingobacterium"   "Rikenella"          "Dyadobacter"       
## [10] "GCA-900066225"      "UBA1819"            "Oscillibacter"

## [1] "Families in stomach tube samples not in grab samples"

##  [1] "Coprococcus_3"                "Lachnospiraceae_NC2004_group"
##  [3] "Cellulosilyticum"             "Clostridioides"              
##  [5] "Filifactor"                   "Parvimonas"                  
##  [7] "Gallicola"                    "Kandleria"                   
##  [9] "Jeotgalibaca"                 "Aeribacillus"                
## [11] "Cellvibrio"                   "Alysiella"                   
## [13] "Xylophilus"                   "Verticia"                    
## [15] "Oligella"                     "Moraxella"                   
## [17] "Caviibacter"                  "Bilophila"                   
## [19] "Bifidobacterium"              "Rathayibacter"               
## [21] "Curtobacterium"               "Clavibacter"                 
## [23] "Leucobacter"                  "Kocuria"                     
## [25] "Parvibacter"                  "Harryflintia"                
## [27] "Fournierella"                 "Oscillospira"

##  [1] "Sellimonas"         "Incertae_Sedis"     "Sarcina"           
##  [4] "Rhodobacter"        "Ketogulonicigenium" "Sphingobium"       
##  [7] "Sphingobacterium"   "Rikenella"          "Dyadobacter"       
## [10] "GCA-900066225"      "UBA1819"            "Oscillibacter"

These the 12 genera found in the grab sample, but not the stomach tube.

##  [1] "Lachnospiraceae"                 "Defluviitaleaceae"              
##  [3] NA                                "Ruminococcaceae"                
##  [5] "Veillonellaceae"                 "Peptostreptococcaceae"          
##  [7] "Family_XIII"                     "Family_XI"                      
##  [9] "Clostridiales_vadinBB60_group"   "Anaeroplasmataceae"             
## [11] "Erysipelotrichaceae"             "Mycoplasmataceae"               
## [13] "Streptococcaceae"                "Leuconostocaceae"               
## [15] "Lactobacillaceae"                "Enterococcaceae"                
## [17] "Carnobacteriaceae"               "Aerococcaceae"                  
## [19] "Staphylococcaceae"               "Planococcaceae"                 
## [21] "Bacillaceae"                     "Peptococcaceae"                 
## [23] "Christensenellaceae"             "Clostridiaceae_1"               
## [25] "Acidaminococcaceae"              "Syntrophomonadaceae"            
## [27] "Eubacteriaceae"                  "Puniceicoccaceae"               
## [29] "Pedosphaeraceae"                 "Akkermansiaceae"                
## [31] "Campylobacteraceae"              "Elusimicrobiaceae"              
## [33] "Pirellulaceae"                   "Saccharimonadaceae"             
## [35] "Endomicrobiaceae"                "Xanthomonadaceae"               
## [37] "Pseudomonadaceae"                "Succinivibrionaceae"            
## [39] "Enterobacteriaceae"              "Burkholderiaceae"               
## [41] "Cardiobacteriaceae"              "Pasteurellaceae"                
## [43] "Moraxellaceae"                   "Desulfobulbaceae"               
## [45] "Oligoflexaceae"                  "Paracaedibacteraceae"           
## [47] "Leptotrichiaceae"                "Fusobacteriaceae"               
## [49] "Methanobacteriaceae"             "Methanomethylophilaceae"        
## [51] "Methanocorpusculaceae"           "Devosiaceae"                    
## [53] "Sphingomonadaceae"               "Rhizobiaceae"                   
## [55] "Beijerinckiaceae"                "Caulobacteraceae"               
## [57] "Desulfovibrionaceae"             "Desulfuromonadaceae"            
## [59] "Spirochaetaceae"                 "vadinBE97"                      
## [61] "Victivallaceae"                  "Beutenbergiaceae"               
## [63] "Microbacteriaceae"               "Sanguibacteraceae"              
## [65] "Corynebacteriaceae"              "Nocardiaceae"                   
## [67] "Nocardioidaceae"                 "Coriobacteriales_Incertae_Sedis"
## [69] "Eggerthellaceae"                 "Atopobiaceae"                   
## [71] "Fibrobacteraceae"                "Anaerolineaceae"                
## [73] "0319-6G20"                       "Synergistaceae"                 
## [75] "Prevotellaceae"                  "Bacteroidales_UCG-001"          
## [77] "Bacteroidaceae"                  "p-251-o5"                       
## [79] "Muribaculaceae"                  "Marinifilaceae"                 
## [81] "F082"                            "Rikenellaceae"                  
## [83] "Bacteroidetes_BD2-2"             "Sphingobacteriaceae"            
## [85] "PeH15"                           "M2PB4-65_termite_group"         
## [87] "Bacteroidales_BS11_gut_group"    "COB_P4-1_termite_group"         
## [89] "Marinilabiliaceae"               "Tannerellaceae"                 
## [91] "Paludibacteraceae"               "Porphyromonadaceae"             
## [93] "Bacteroidales_RF16_group"

##   [1] "Lachnospiraceae_AC2044_group"                      
##   [2] NA                                                  
##   [3] "Lachnospiraceae_NK4A136_group"                     
##   [4] "Lachnospiraceae_FE2018_group"                      
##   [5] "Lachnospiraceae_ND3007_group"                      
##   [6] "Acetatifactor"                                     
##   [7] "Acetitomaculum"                                    
##   [8] "Oribacterium"                                      
##   [9] "Howardella"                                        
##  [10] "Lachnospiraceae_UCG-009"                           
##  [11] "Dorea"                                             
##  [12] "Marvinbryantia"                                    
##  [13] "Lachnoclostridium_10"                              
##  [14] "Fusicatenibacter"                                  
##  [15] "Blautia"                                           
##  [16] "Lachnospiraceae_NK3A20_group"                      
##  [17] "Lachnospiraceae_XPB1014_group"                     
##  [18] "Lachnospiraceae_UCG-006"                           
##  [19] "XBB1006"                                           
##  [20] "Roseburia"                                         
##  [21] "Shuttleworthia"                                    
##  [22] "Lachnoclostridium"                                 
##  [23] "FD2005"                                            
##  [24] "Agathobacter"                                      
##  [25] "Lachnospiraceae_UCG-001"                           
##  [26] "Pseudobutyrivibrio"                                
##  [27] "Tyzzerella_4"                                      
##  [28] "Moryella"                                          
##  [29] "Lachnospiraceae_UCG-002"                           
##  [30] "Syntrophococcus"                                   
##  [31] "Butyrivibrio_2"                                    
##  [32] "Lachnoclostridium_1"                               
##  [33] "Butyrivibrio"                                      
##  [34] "Anaerosporobacter"                                 
##  [35] "Lachnoclostridium_12"                              
##  [36] "Lachnospira"                                       
##  [37] "Lachnospiraceae_FCS020_group"                      
##  [38] "Lachnospiraceae_UCG-008"                           
##  [39] "Lachnospiraceae_NK4B4_group"                       
##  [40] "Coprococcus_2"                                     
##  [41] "Defluviitaleaceae_UCG-011"                         
##  [42] "Lachnospiraceae_UCG-010"                           
##  [43] "Tyzzerella"                                        
##  [44] "Coprococcus_1"                                     
##  [45] "GCA-900066575"                                     
##  [46] "Ruminococcaceae_UCG-014"                           
##  [47] "Tyzzerella_3"                                      
##  [48] "Candidatus_Soleaferrea"                            
##  [49] "Megasphaera"                                       
##  [50] "Veillonellaceae_UCG-001"                           
##  [51] "Quinella"                                          
##  [52] "Selenomonas_1"                                     
##  [53] "Schwartzia"                                        
##  [54] "Selenomonas_4"                                     
##  [55] "Anaerovibrio"                                      
##  [56] "Romboutsia"                                        
##  [57] "Family_XIII_AD3011_group"                          
##  [58] "Mogibacterium"                                     
##  [59] "Anaerovorax"                                       
##  [60] "Family_XIII_UCG-001"                               
##  [61] "Murdochiella"                                      
##  [62] "Helcococcus"                                       
##  [63] "Peptoniphilus"                                     
##  [64] "Anaeroplasma"                                      
##  [65] "Catenisphaera"                                     
##  [66] "Erysipelotrichaceae_UCG-006"                       
##  [67] "Solobacterium"                                     
##  [68] "Erysipelotrichaceae_UCG-009"                       
##  [69] "Erysipelotrichaceae_UCG-008"                       
##  [70] "Erysipelotrichaceae_UCG-004"                       
##  [71] "Erysipelatoclostridium"                            
##  [72] "Mycoplasma"                                        
##  [73] "Streptococcus"                                     
##  [74] "Weissella"                                         
##  [75] "Lactobacillus"                                     
##  [76] "Enterococcus"                                      
##  [77] "Desemzia"                                          
##  [78] "Aerococcus"                                        
##  [79] "Turicibacter"                                      
##  [80] "Staphylococcus"                                    
##  [81] "Planococcus"                                       
##  [82] "Clostridium_sensu_stricto_1"                       
##  [83] "Phascolarctobacterium"                             
##  [84] "Succiniclasticum"                                  
##  [85] "Pelospora"                                         
##  [86] "Eubacterium"                                       
##  [87] "Anaerofustis"                                      
##  [88] "Akkermansia"                                       
##  [89] "Campylobacter"                                     
##  [90] "Elusimicrobium"                                    
##  [91] "p-1088-a5_gut_group"                               
##  [92] "Pirellula"                                         
##  [93] "CPla-4_termite_group"                              
##  [94] "Candidatus_Saccharimonas"                          
##  [95] "Candidatus_Endomicrobium"                          
##  [96] "Thermomonas"                                       
##  [97] "Stenotrophomonas"                                  
##  [98] "Pseudomonas"                                       
##  [99] "Succinimonas"                                      
## [100] "Anaerobiospirillum"                                
## [101] "Succinivibrio"                                     
## [102] "Pantoea"                                           
## [103] "Klebsiella"                                        
## [104] "Sutterella"                                        
## [105] "Variovorax"                                        
## [106] "Limnohabitans"                                     
## [107] "Comamonas"                                         
## [108] "Janthinobacterium"                                 
## [109] "Massilia"                                          
## [110] "Duganella"                                         
## [111] "Suttonella"                                        
## [112] "Bibersteinia"                                      
## [113] "Actinobacillus"                                    
## [114] "Escherichia/Shigella"                              
## [115] "Ruminobacter"                                      
## [116] "Psychrobacter"                                     
## [117] "Acinetobacter"                                     
## [118] "Succinivibrionaceae_UCG-002"                       
## [119] "Desulfobulbus"                                     
## [120] "Leptotrichia"                                      
## [121] "Fusobacterium"                                     
## [122] "Methanobrevibacter"                                
## [123] "Methanosphaera"                                    
## [124] "Candidatus_Methanomethylophilus"                   
## [125] "Methanocorpusculum"                                
## [126] "Devosia"                                           
## [127] "Sphingomonas"                                      
## [128] "Novosphingobium"                                   
## [129] "Ochrobactrum"                                      
## [130] "Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium"
## [131] "Neorhizobium"                                      
## [132] "Chelativorans"                                     
## [133] "Methylobacterium"                                  
## [134] "Brevundimonas"                                     
## [135] "Desulfovibrio"                                     
## [136] "Mailhella"                                         
## [137] "Desulfuromonas"                                    
## [138] "M2PT2-76_termite_group"                            
## [139] "Sediminispirochaeta"                               
## [140] "Treponema_2"                                       
## [141] "Salana"                                            
## [142] "Pseudoclavibacter"                                 
## [143] "Galbitalea"                                        
## [144] "Frigoribacterium"                                  
## [145] "Sanguibacter"                                      
## [146] "Corynebacterium_1"                                 
## [147] "Corynebacterium"                                   
## [148] "Rhodococcus"                                       
## [149] "Aeromicrobium"                                     
## [150] "Raoultibacter"                                     
## [151] "Denitrobacterium"                                  
## [152] "DNF00809"                                          
## [153] "Slackia"                                           
## [154] "Atopobium"                                         
## [155] "Olsenella"                                         
## [156] "Fibrobacter"                                       
## [157] "Flexilinea"                                        
## [158] "Synergistes"                                       
## [159] "Fretibacterium"                                    
## [160] "Pyramidobacter"                                    
## [161] "Christensenellaceae_R-7_group"                     
## [162] "Ruminococcaceae_UCG-010"                           
## [163] "Prevotellaceae_UCG-003"                            
## [164] "Alloprevotella"                                    
## [165] "Prevotellaceae_UCG-004"                            
## [166] "Prevotellaceae_UCG-001"                            
## [167] "Prevotellaceae_Ga6A1_group"                        
## [168] "Prevotella_1"                                      
## [169] "Prevotellaceae_NK3B31_group"                       
## [170] "Prevotellaceae_YAB2003_group"                      
## [171] "Bacteroides"                                       
## [172] "Rikenellaceae_RC9_gut_group"                       
## [173] "dgA-11_gut_group"                                  
## [174] "U29-B03"                                           
## [175] "Pedobacter"                                        
## [176] "Alistipes"                                         
## [177] "Tannerella"                                        
## [178] "Parabacteroides"                                   
## [179] "Porphyromonas"                                     
## [180] "hoa5-07d05_gut_group"                              
## [181] "Ruminiclostridium_6"                               
## [182] "Ruminococcus_1"                                    
## [183] "Angelakisella"                                     
## [184] "Ruminiclostridium"                                 
## [185] "Hydrogenoanaerobacterium"                          
## [186] "Subdoligranulum"                                   
## [187] "Caproiciproducens"                                 
## [188] "Ruminococcus_2"                                    
## [189] "Ruminococcaceae_UCG-001"                           
## [190] "Ruminiclostridium_5"                               
## [191] "CAG-352"                                           
## [192] "Saccharofermentans"                                
## [193] "Ruminiclostridium_1"                               
## [194] "Ruminococcaceae_UCG-012"                           
## [195] "Ruminococcaceae_UCG-013"                           
## [196] "Ruminococcaceae_UCG-009"                           
## [197] "Ruminococcaceae_NK4A214_group"                     
## [198] "Papillibacter"                                     
## [199] "Ruminococcaceae_UCG-007"                           
## [200] "Ruminococcaceae_V9D2013_group"                     
## [201] "Sporobacter"                                       
## [202] "Ruminococcaceae_UCG-005"                           
## [203] "Ruminococcaceae_UCG-004"                           
## [204] "Ruminococcaceae_UCG-002"                           
## [205] "Ruminiclostridium_9"                               
## [206] "Flavonifractor"                                    
## [207] "possible_genus_Sk018"                              
## [208] "probable_genus_10"

These are the 208 genera that are found in both the grab sample and stomach tube.

There are 255 ASVs are found in the grab samples, but not found in the stomach tube samples and 404 are found in the stomach tube samples, but not found in the grab samples. There is also 3615 ASVs found in common between grab samples and stomach tube samples. Let’s check at a higher taxonomic rank next.

Let’s compare the stomach tube samples to the “gold standard” of grab sample.

There are 199 ASVs and 43 genera and 13 significant differentially abundant between stomach tube and grab samples.

Unique Genera that are significant differentially abundant
x
Firmicutes_Lachnospiraceae_Lachnospiraceae_ND3007_group
Firmicutes_Lachnospiraceae_Lachnospiraceae_NK4A136_group
Firmicutes_Lachnospiraceae_Acetatifactor
Firmicutes_Lachnospiraceae_Oribacterium
Firmicutes_Lachnospiraceae_Howardella
Firmicutes_Lachnospiraceae_Blautia
Firmicutes_Lachnospiraceae_XBB1006
Firmicutes_Lachnospiraceae_Shuttleworthia
Firmicutes_Lachnospiraceae_Pseudobutyrivibrio
Firmicutes_Lachnospiraceae_Lachnospiraceae_AC2044_group_bacterium
Firmicutes_Lachnospiraceae_Butyrivibrio_2
Firmicutes_Lachnospiraceae_Acetitomaculum
Firmicutes_Lachnospiraceae_Lachnoclostridium_10
Firmicutes_Lachnospiraceae_Coprococcus_2
Firmicutes_Lachnospiraceae_Lachnospiraceae_FCS020_group_bacterium
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-014
Firmicutes_Family_XIII_Mogibacterium
Firmicutes_Erysipelotrichaceae_Catenisphaera
Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
Firmicutes_Streptococcaceae_Streptococcus
Firmicutes_Lactobacillaceae_Lactobacillus
Proteobacteria_Cardiobacteriaceae_Suttonella
Euryarchaeota_Methanobacteriaceae_Methanobrevibacter
Spirochaetes_Spirochaetaceae_Sediminispirochaeta
Actinobacteria_Atopobiaceae_Olsenella
Fibrobacteres_Fibrobacteraceae_Fibrobacter_succinogenes
Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-003
Bacteroidetes_Prevotellaceae_Prevotellaceae_Ga6A1_group
Bacteroidetes_Prevotellaceae_Prevotellaceae_NK3B31_group
Firmicutes_Ruminococcaceae_Ruminococcus_1
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-001
Firmicutes_Ruminococcaceae_Ruminococcus_2
Firmicutes_Ruminococcaceae_CAG-352
Firmicutes_Ruminococcaceae_Saccharofermentans
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-013
Firmicutes_Ruminococcaceae_Ruminococcaceae_NK4A214_group
Firmicutes_Ruminococcaceae_Ruminiclostridium_9
Firmicutes_Ruminococcaceae_Ruminococcaceae_V9D2013_group
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-004
Firmicutes_Lachnospiraceae_Lachnospiraceae_XPB1014_group
Firmicutes_Lachnospiraceae_possible_genus_Sk018
Firmicutes_Lachnospiraceae_probable_genus_10

These are the the unique genera that are significant differentially abundant between grab and stomach tube samples.

# of significant genera in each family
Var1	Freq
Firmicutes_Lachnospiraceae	54
Firmicutes_Ruminococcaceae	31
Bacteroidetes_Prevotellaceae	25
Firmicutes_Christensenellaceae	17
Fibrobacteres_Fibrobacteraceae	16
Bacteroidetes_Rikenellaceae	8
Spirochaetes_Spirochaetaceae	8
Euryarchaeota_Methanobacteriaceae	4
Firmicutes_Erysipelotrichaceae	4
Kiritimatiellaeota	4
Lentisphaerae_vadinBE97	4
Bacteroidetes_F082	3
Firmicutes_Family_XIII	3
Actinobacteria_Atopobiaceae	2
Bacteroidetes_Bacteroidales_BS11_gut_group	2
Actinobacteria_Eggerthellaceae	1
Bacteroidetes	1
Bacteroidetes_Bacteroidales_RF16_group	1
Bacteroidetes_Bacteroidetes_BD2-2	1
Bacteroidetes_Muribaculaceae	1
Bacteroidetes_p-251-o5	1
Cyanobacteria	1
Euryarchaeota_Methanomethylophilaceae	1
Firmicutes_Streptococcaceae	1
Patescibacteria	1
Proteobacteria_Burkholderiaceae	1
Proteobacteria_Succinivibrionaceae	1
Tenericutes	1
Verrucomicrobia	1

From this we can see that Lachnospiraceae, Ruminococcaceae, Prevotellaceae and Erysipelotrichaceae were the most common families to have significant differentially abundant ASVs in grab vs stomach tube samples. We will take a closer look at all ASVs differentially abundant.

## 
## -1  1 
## 21 10

This is the number of ASVs in the family Lachnospiraceae that are positively and negatively associated in stomach tube samples.

## 
## -1  1 
## 15  3

	x	Family	Genus
7	-1.3060006	Lachnospiraceae	XBB1006
3	-1.2804052	Lachnospiraceae	Acetatifactor
13	-1.0189351	Lachnospiraceae	Lachnoclostridium_10
14	-0.9426866	Lachnospiraceae	Coprococcus_2
15	-0.9321014	Lachnospiraceae	Lachnospiraceae_FCS020_group
18	-0.9037477	Lachnospiraceae	probable_genus_10
1	-0.8064012	Lachnospiraceae	Lachnospiraceae_ND3007_group
8	-0.7601064	Lachnospiraceae	Shuttleworthia
10	-0.7250690	Lachnospiraceae	Lachnospiraceae_AC2044_group
2	-0.6223167	Lachnospiraceae	Lachnospiraceae_NK4A136_group
9	-0.5251488	Lachnospiraceae	Pseudobutyrivibrio
17	-0.4515620	Lachnospiraceae	possible_genus_Sk018
11	-0.2900656	Lachnospiraceae	Butyrivibrio_2
16	-0.2899893	Lachnospiraceae	Lachnospiraceae_XPB1014_group
4	-0.2788123	Lachnospiraceae	Oribacterium
6	0.3521225	Lachnospiraceae	Blautia
12	0.3915896	Lachnospiraceae	Acetitomaculum
5	1.8266653	Lachnospiraceae	Howardella

Going to check if there are an Euryarchaeota that are only found in one sample type.

## Taxonomy Table:     [32 taxa by 7 taxonomic ranks]:
##          Kingdom   Phylum          Class            
## ASV_1308 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1441 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4053 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_5508 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_7    "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_184  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3038 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3184 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_264  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_710  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4546 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4863 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_24   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1749 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_88   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1703 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_84   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1323 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_484  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_599  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3860 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1114 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_948  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_700  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3066 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_54   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_5586 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_58   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3936 "Archaea" "Euryarchaeota" "Thermoplasmata" 
## ASV_5594 "Archaea" "Euryarchaeota" "Methanomicrobia"
## ASV_1434 "Archaea" "Euryarchaeota" "Methanomicrobia"
## ASV_4298 "Archaea" "Euryarchaeota" "Methanomicrobia"
##          Order                     Family                   
## ASV_1308 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1441 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_4053 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_5508 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_7    "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_184  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3038 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3184 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_264  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_710  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_4546 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_4863 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_24   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1749 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_88   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1703 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_84   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1323 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_484  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_599  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3860 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1114 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_948  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_700  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3066 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_54   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_5586 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_58   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3936 "Methanomassiliicoccales" "Methanomethylophilaceae"
## ASV_5594 "Methanosarcinales"       "Methanosarcinaceae"     
## ASV_1434 "Methanomicrobiales"      "Methanocorpusculaceae"  
## ASV_4298 "Methanomicrobiales"      "Methanocorpusculaceae"  
##          Genus                             Species
## ASV_1308 "Methanobrevibacter"              NA     
## ASV_1441 "Methanobrevibacter"              NA     
## ASV_4053 "Methanobrevibacter"              NA     
## ASV_5508 "Methanobrevibacter"              NA     
## ASV_7    "Methanobrevibacter"              NA     
## ASV_184  "Methanosphaera"                  NA     
## ASV_3038 "Methanosphaera"                  NA     
## ASV_3184 "Methanosphaera"                  NA     
## ASV_264  "Methanosphaera"                  NA     
## ASV_710  "Methanosphaera"                  NA     
## ASV_4546 "Methanobrevibacter"              NA     
## ASV_4863 "Methanobrevibacter"              NA     
## ASV_24   "Methanobrevibacter"              NA     
## ASV_1749 "Methanobrevibacter"              NA     
## ASV_88   "Methanobrevibacter"              NA     
## ASV_1703 "Methanobrevibacter"              NA     
## ASV_84   "Methanobrevibacter"              NA     
## ASV_1323 "Methanobrevibacter"              NA     
## ASV_484  "Methanobrevibacter"              NA     
## ASV_599  "Methanobrevibacter"              NA     
## ASV_3860 "Methanobrevibacter"              NA     
## ASV_1114 "Methanobrevibacter"              NA     
## ASV_948  "Methanobrevibacter"              NA     
## ASV_700  "Methanobrevibacter"              NA     
## ASV_3066 "Methanobrevibacter"              NA     
## ASV_54   "Methanobrevibacter"              NA     
## ASV_5586 "Methanobrevibacter"              NA     
## ASV_58   "Methanobrevibacter"              NA     
## ASV_3936 "Candidatus_Methanomethylophilus" NA     
## ASV_5594 "Methanimicrococcus"              NA     
## ASV_1434 "Methanocorpusculum"              NA     
## ASV_4298 "Methanocorpusculum"              NA

##  [1] Stomach Tube      Stomach Tube      Stomach Tube     
##  [4] Stomach Tube      Stomach Tube      Stomach Tube     
##  [7] Stomach Tube      Stomach Tube      Stomach Tube     
## [10] Stomach Tube      Stomach Tube      Grab Sample      
## [13] Grab Sample       Grab Sample       Grab Sample      
## [16] Grab Sample       Grab Sample       Grab Sample      
## [19] Grab Sample       Grab Sample       Grab Sample      
## [22] Grab Sample       Grab Sample       Liquid Strained  
## [25] Liquid Strained   Liquid Strained   Liquid Strained  
## [28] Liquid Strained   Liquid Strained   Liquid Strained  
## [31] Stomach Tube      Liquid Unstrained Liquid Unstrained
## [34] Liquid Unstrained Liquid Unstrained Liquid Unstrained
## [37] Liquid Unstrained Feces             Feces            
## [40] Feces             Solid             Solid            
## [43] Solid             Solid             Solid            
## [46] Solid             Solid             Solid            
## [49] Solid             Solid             Solid            
## [52] Solid             Liquid Strained   Liquid Strained  
## [55] Liquid Strained   Liquid Strained   Liquid Strained  
## [58] Liquid Unstrained Liquid Unstrained
## 6 Levels: Grab Sample Feces Stomach Tube Liquid Strained ... Liquid Unstrained

## OTU Table:          [1 taxa and 59 samples]
##                      taxa are rows
##         282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_231  18  30  10  12  16   4  11   6  12   9  13  17   6   4   9  10
##         298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_231   8  16  16  10   6  11   6  14   6   7  30  23  22   5  10  12
##         360 361 362 363 365 368 371 373 379 380 381 382 383 384 385 386
## ASV_231  17  17  14   8  19   2   1   1  25  38  15  45  18  24  15  53
##         387 388 389 390 505 506 507 508 509 510 511
## ASV_231  38  23  34   6   9  19   8   2  63  42  35

These are the genera that are significant differentially abundant genera in stomach tube vs grab samples.

## [1] NA            "Fibrobacter"

The only assigned genera in the family Fibrobacteraceae, Fibrobacter was significantly lower in abundance in stomach tubes compared to grab samples.

x	Phylum	Family	Genus
-1.8769355	Fibrobacteres	Fibrobacteraceae	Fibrobacter
-1.3060006	Firmicutes	Lachnospiraceae	XBB1006
-1.2804052	Firmicutes	Lachnospiraceae	Acetatifactor
-1.0189351	Firmicutes	Lachnospiraceae	Lachnoclostridium_10
-0.9426866	Firmicutes	Lachnospiraceae	Coprococcus_2
-0.9321014	Firmicutes	Lachnospiraceae	Lachnospiraceae_FCS020_group
-0.9037477	Firmicutes	Lachnospiraceae	probable_genus_10
-0.8739379	Bacteroidetes	Prevotellaceae	Prevotellaceae_Ga6A1_group
-0.8064012	Firmicutes	Lachnospiraceae	Lachnospiraceae_ND3007_group
-0.7661424	Firmicutes	Ruminococcaceae	Ruminococcus_1
-0.7601064	Firmicutes	Lachnospiraceae	Shuttleworthia
-0.7250690	Firmicutes	Lachnospiraceae	Lachnospiraceae_AC2044_group
-0.7159013	Spirochaetes	Spirochaetaceae	Sediminispirochaeta
-0.6223167	Firmicutes	Lachnospiraceae	Lachnospiraceae_NK4A136_group
-0.5577767	Bacteroidetes	Prevotellaceae	Prevotellaceae_NK3B31_group
-0.5251488	Firmicutes	Lachnospiraceae	Pseudobutyrivibrio
-0.4677556	Firmicutes	Ruminococcaceae	Saccharofermentans
-0.4515620	Firmicutes	Lachnospiraceae	possible_genus_Sk018
-0.3024765	Firmicutes	Ruminococcaceae	Ruminococcaceae_UCG-014
-0.2900656	Firmicutes	Lachnospiraceae	Butyrivibrio_2
-0.2899893	Firmicutes	Lachnospiraceae	Lachnospiraceae_XPB1014_group
-0.2788123	Firmicutes	Lachnospiraceae	Oribacterium
0.3193401	Euryarchaeota	Methanobacteriaceae	Methanobrevibacter
0.3521225	Firmicutes	Lachnospiraceae	Blautia
0.3735289	Firmicutes	Family_XIII	Mogibacterium
0.3767681	Bacteroidetes	Prevotellaceae	Prevotellaceae_UCG-003
0.3915896	Firmicutes	Lachnospiraceae	Acetitomaculum
0.4050196	Firmicutes	Ruminococcaceae	Ruminococcaceae_NK4A214_group
0.4068741	Firmicutes	Ruminococcaceae	Ruminococcaceae_UCG-004
0.4091719	Firmicutes	Ruminococcaceae	Ruminococcus_2
0.4213922	Firmicutes	Ruminococcaceae	Ruminococcaceae_V9D2013_group
0.6291728	Firmicutes	Erysipelotrichaceae	Catenisphaera
0.7125459	Firmicutes	Ruminococcaceae	Ruminococcaceae_UCG-001
0.7537462	Actinobacteria	Atopobiaceae	Olsenella
0.7998338	Firmicutes	Lactobacillaceae	Lactobacillus
0.9805989	Firmicutes	Erysipelotrichaceae	Erysipelotrichaceae_UCG-009
1.0394506	Firmicutes	Ruminococcaceae	Ruminococcaceae_UCG-013
1.1037244	Firmicutes	Ruminococcaceae	Ruminiclostridium_9
1.1678026	Firmicutes	Erysipelotrichaceae	Erysipelotrichaceae_UCG-004
1.5268279	Firmicutes	Ruminococcaceae	CAG-352
1.6367580	Proteobacteria	Cardiobacteriaceae	Suttonella
1.8266653	Firmicutes	Lachnospiraceae	Howardella
1.8417467	Firmicutes	Streptococcaceae	Streptococcus

Grab vs liquid strained samples

Let’s compare the liquid strained samples to the “gold standard” of grab sample.

There are 283 ASVs are found in the grab sample, but not found in the liquid strained samples. There is also 3587 ASVs found in common between grab samples. Thus, stomach tube samples tend to be more like a grab sample than a strained sample. Let’s check at a higher taxonomic rank next.

## [1] "Sellimonas"               "Tyzzerella"              
## [3] "Desemzia"                 "Limnohabitans"           
## [5] "Leptotrichia"             "Salana"                  
## [7] "Rikenella"                "GCA-900066225"           
## [9] "Hydrogenoanaerobacterium"

These genera are found in the grab sample, but not the stomach tube.

##   [1] "Lachnospiraceae_AC2044_group"                      
##   [2] NA                                                  
##   [3] "Lachnospiraceae_NK4A136_group"                     
##   [4] "Lachnospiraceae_FE2018_group"                      
##   [5] "Lachnospiraceae_ND3007_group"                      
##   [6] "Acetatifactor"                                     
##   [7] "Acetitomaculum"                                    
##   [8] "Oribacterium"                                      
##   [9] "Howardella"                                        
##  [10] "Lachnospiraceae_UCG-009"                           
##  [11] "Dorea"                                             
##  [12] "Marvinbryantia"                                    
##  [13] "Lachnoclostridium_10"                              
##  [14] "Fusicatenibacter"                                  
##  [15] "Blautia"                                           
##  [16] "Lachnospiraceae_NK3A20_group"                      
##  [17] "Lachnospiraceae_XPB1014_group"                     
##  [18] "Lachnospiraceae_UCG-006"                           
##  [19] "XBB1006"                                           
##  [20] "Roseburia"                                         
##  [21] "Shuttleworthia"                                    
##  [22] "Lachnoclostridium"                                 
##  [23] "FD2005"                                            
##  [24] "Agathobacter"                                      
##  [25] "Lachnospiraceae_UCG-001"                           
##  [26] "Pseudobutyrivibrio"                                
##  [27] "Tyzzerella_4"                                      
##  [28] "Moryella"                                          
##  [29] "Lachnospiraceae_UCG-002"                           
##  [30] "Syntrophococcus"                                   
##  [31] "Butyrivibrio_2"                                    
##  [32] "Lachnoclostridium_1"                               
##  [33] "Butyrivibrio"                                      
##  [34] "Anaerosporobacter"                                 
##  [35] "Lachnoclostridium_12"                              
##  [36] "Lachnospira"                                       
##  [37] "Lachnospiraceae_FCS020_group"                      
##  [38] "Lachnospiraceae_UCG-008"                           
##  [39] "Lachnospiraceae_NK4B4_group"                       
##  [40] "Coprococcus_2"                                     
##  [41] "Defluviitaleaceae_UCG-011"                         
##  [42] "Lachnospiraceae_UCG-010"                           
##  [43] "Coprococcus_1"                                     
##  [44] "GCA-900066575"                                     
##  [45] "Incertae_Sedis"                                    
##  [46] "Ruminococcaceae_UCG-014"                           
##  [47] "Tyzzerella_3"                                      
##  [48] "Candidatus_Soleaferrea"                            
##  [49] "Megasphaera"                                       
##  [50] "Veillonellaceae_UCG-001"                           
##  [51] "Quinella"                                          
##  [52] "Selenomonas_1"                                     
##  [53] "Schwartzia"                                        
##  [54] "Selenomonas_4"                                     
##  [55] "Anaerovibrio"                                      
##  [56] "Romboutsia"                                        
##  [57] "Family_XIII_AD3011_group"                          
##  [58] "Mogibacterium"                                     
##  [59] "Anaerovorax"                                       
##  [60] "Family_XIII_UCG-001"                               
##  [61] "Murdochiella"                                      
##  [62] "Helcococcus"                                       
##  [63] "Peptoniphilus"                                     
##  [64] "Anaeroplasma"                                      
##  [65] "Catenisphaera"                                     
##  [66] "Erysipelotrichaceae_UCG-006"                       
##  [67] "Solobacterium"                                     
##  [68] "Erysipelotrichaceae_UCG-009"                       
##  [69] "Erysipelotrichaceae_UCG-008"                       
##  [70] "Erysipelotrichaceae_UCG-004"                       
##  [71] "Erysipelatoclostridium"                            
##  [72] "Mycoplasma"                                        
##  [73] "Streptococcus"                                     
##  [74] "Weissella"                                         
##  [75] "Lactobacillus"                                     
##  [76] "Enterococcus"                                      
##  [77] "Aerococcus"                                        
##  [78] "Turicibacter"                                      
##  [79] "Staphylococcus"                                    
##  [80] "Planococcus"                                       
##  [81] "Clostridium_sensu_stricto_1"                       
##  [82] "Sarcina"                                           
##  [83] "Phascolarctobacterium"                             
##  [84] "Succiniclasticum"                                  
##  [85] "Pelospora"                                         
##  [86] "Eubacterium"                                       
##  [87] "Anaerofustis"                                      
##  [88] "Akkermansia"                                       
##  [89] "Campylobacter"                                     
##  [90] "Elusimicrobium"                                    
##  [91] "p-1088-a5_gut_group"                               
##  [92] "Pirellula"                                         
##  [93] "CPla-4_termite_group"                              
##  [94] "Candidatus_Saccharimonas"                          
##  [95] "Candidatus_Endomicrobium"                          
##  [96] "Thermomonas"                                       
##  [97] "Stenotrophomonas"                                  
##  [98] "Pseudomonas"                                       
##  [99] "Succinimonas"                                      
## [100] "Anaerobiospirillum"                                
## [101] "Succinivibrio"                                     
## [102] "Pantoea"                                           
## [103] "Klebsiella"                                        
## [104] "Sutterella"                                        
## [105] "Variovorax"                                        
## [106] "Comamonas"                                         
## [107] "Janthinobacterium"                                 
## [108] "Massilia"                                          
## [109] "Duganella"                                         
## [110] "Suttonella"                                        
## [111] "Bibersteinia"                                      
## [112] "Actinobacillus"                                    
## [113] "Escherichia/Shigella"                              
## [114] "Ruminobacter"                                      
## [115] "Psychrobacter"                                     
## [116] "Acinetobacter"                                     
## [117] "Succinivibrionaceae_UCG-002"                       
## [118] "Desulfobulbus"                                     
## [119] "Fusobacterium"                                     
## [120] "Methanobrevibacter"                                
## [121] "Methanosphaera"                                    
## [122] "Candidatus_Methanomethylophilus"                   
## [123] "Methanocorpusculum"                                
## [124] "Rhodobacter"                                       
## [125] "Ketogulonicigenium"                                
## [126] "Devosia"                                           
## [127] "Sphingomonas"                                      
## [128] "Novosphingobium"                                   
## [129] "Sphingobium"                                       
## [130] "Ochrobactrum"                                      
## [131] "Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium"
## [132] "Neorhizobium"                                      
## [133] "Chelativorans"                                     
## [134] "Methylobacterium"                                  
## [135] "Brevundimonas"                                     
## [136] "Desulfovibrio"                                     
## [137] "Mailhella"                                         
## [138] "Desulfuromonas"                                    
## [139] "M2PT2-76_termite_group"                            
## [140] "Sediminispirochaeta"                               
## [141] "Treponema_2"                                       
## [142] "Pseudoclavibacter"                                 
## [143] "Galbitalea"                                        
## [144] "Frigoribacterium"                                  
## [145] "Sanguibacter"                                      
## [146] "Corynebacterium_1"                                 
## [147] "Corynebacterium"                                   
## [148] "Rhodococcus"                                       
## [149] "Aeromicrobium"                                     
## [150] "Raoultibacter"                                     
## [151] "Denitrobacterium"                                  
## [152] "DNF00809"                                          
## [153] "Slackia"                                           
## [154] "Atopobium"                                         
## [155] "Olsenella"                                         
## [156] "Fibrobacter"                                       
## [157] "Flexilinea"                                        
## [158] "Synergistes"                                       
## [159] "Fretibacterium"                                    
## [160] "Pyramidobacter"                                    
## [161] "Christensenellaceae_R-7_group"                     
## [162] "Ruminococcaceae_UCG-010"                           
## [163] "Prevotellaceae_UCG-003"                            
## [164] "Alloprevotella"                                    
## [165] "Prevotellaceae_UCG-004"                            
## [166] "Prevotellaceae_UCG-001"                            
## [167] "Prevotellaceae_Ga6A1_group"                        
## [168] "Prevotella_1"                                      
## [169] "Prevotellaceae_NK3B31_group"                       
## [170] "Prevotellaceae_YAB2003_group"                      
## [171] "Bacteroides"                                       
## [172] "Rikenellaceae_RC9_gut_group"                       
## [173] "dgA-11_gut_group"                                  
## [174] "U29-B03"                                           
## [175] "Sphingobacterium"                                  
## [176] "Pedobacter"                                        
## [177] "Alistipes"                                         
## [178] "Dyadobacter"                                       
## [179] "Tannerella"                                        
## [180] "Parabacteroides"                                   
## [181] "Porphyromonas"                                     
## [182] "hoa5-07d05_gut_group"                              
## [183] "Ruminiclostridium_6"                               
## [184] "Ruminococcus_1"                                    
## [185] "Angelakisella"                                     
## [186] "Ruminiclostridium"                                 
## [187] "Subdoligranulum"                                   
## [188] "UBA1819"                                           
## [189] "Caproiciproducens"                                 
## [190] "Ruminococcus_2"                                    
## [191] "Ruminococcaceae_UCG-001"                           
## [192] "Ruminiclostridium_5"                               
## [193] "CAG-352"                                           
## [194] "Saccharofermentans"                                
## [195] "Ruminiclostridium_1"                               
## [196] "Ruminococcaceae_UCG-012"                           
## [197] "Ruminococcaceae_UCG-013"                           
## [198] "Ruminococcaceae_UCG-009"                           
## [199] "Ruminococcaceae_NK4A214_group"                     
## [200] "Papillibacter"                                     
## [201] "Ruminococcaceae_UCG-007"                           
## [202] "Ruminococcaceae_V9D2013_group"                     
## [203] "Sporobacter"                                       
## [204] "Ruminococcaceae_UCG-005"                           
## [205] "Ruminococcaceae_UCG-004"                           
## [206] "Oscillibacter"                                     
## [207] "Ruminococcaceae_UCG-002"                           
## [208] "Ruminiclostridium_9"                               
## [209] "Flavonifractor"                                    
## [210] "possible_genus_Sk018"                              
## [211] "probable_genus_10"

These are the 211 genera that are found in both the grab sample and liquid strained samples.

Since we saw that liquid strained samples were distinguished from other rumen samples by Kiritimatiellaeota on the DPCoA we will investigate that further.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 180 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 180 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 180 tips and 179 internal nodes ]

## [1] "Kiritimatiellae_WCHB1-41"

There are 180 ASVs assigned to the phylum Kiritimatiellaeota and these ASVs are only assigned down to the order level. Due to this you won’t find these taxa in the corncob data that was run on genera.

##  [1] Stomach Tube      Stomach Tube      Stomach Tube     
##  [4] Stomach Tube      Stomach Tube      Stomach Tube     
##  [7] Stomach Tube      Stomach Tube      Stomach Tube     
## [10] Stomach Tube      Stomach Tube      Grab Sample      
## [13] Grab Sample       Grab Sample       Grab Sample      
## [16] Grab Sample       Grab Sample       Grab Sample      
## [19] Grab Sample       Grab Sample       Grab Sample      
## [22] Grab Sample       Grab Sample       Liquid Strained  
## [25] Liquid Strained   Liquid Strained   Liquid Strained  
## [28] Liquid Strained   Liquid Strained   Liquid Strained  
## [31] Stomach Tube      Liquid Unstrained Liquid Unstrained
## [34] Liquid Unstrained Liquid Unstrained Liquid Unstrained
## [37] Liquid Unstrained Feces             Feces            
## [40] Feces             Feces             Feces            
## [43] Feces             Feces             Feces            
## [46] Feces             Feces             Feces            
## [49] Feces             Solid             Solid            
## [52] Solid             Solid             Solid            
## [55] Solid             Solid             Solid            
## [58] Solid             Solid             Solid            
## [61] Solid             Liquid Strained   Liquid Strained  
## [64] Liquid Strained   Liquid Strained   Liquid Strained  
## [67] Liquid Unstrained Liquid Unstrained
## 6 Levels: Grab Sample Feces Stomach Tube Liquid Strained ... Liquid Unstrained

The phylum Kiritimatiellaeota is found in all sample types.

There are 180 ASVs assigned to the phylum Kiritimatiellaeota, 17 of these ASVs were significant differentially abundant.

# of significant genera in each family
Var1	Freq
Firmicutes_Lachnospiraceae	25
Firmicutes_Ruminococcaceae	15
Bacteroidetes_Prevotellaceae	6
Firmicutes_Veillonellaceae	5
Proteobacteria_Succinivibrionaceae	5
Firmicutes_Erysipelotrichaceae	4
Firmicutes_Family_XIII	3
Bacteroidetes_Rikenellaceae	2
Proteobacteria_Desulfovibrionaceae	2
Synergistetes_Synergistaceae	2
Actinobacteria_Atopobiaceae	1
Actinobacteria_Coriobacteriales_Incertae_Sedis	1
Actinobacteria_Eggerthellaceae	1
Elusimicrobia_Elusimicrobiaceae	1
Elusimicrobia_Endomicrobiaceae	1
Epsilonbacteraeota_Campylobacteraceae	1
Euryarchaeota_Methanobacteriaceae	1
Firmicutes_Christensenellaceae	1
Firmicutes_Defluviitaleaceae	1
Firmicutes_Eubacteriaceae	1
Firmicutes_Streptococcaceae	1
Planctomycetes_Pirellulaceae	1
Proteobacteria_Burkholderiaceae	1
Proteobacteria_Desulfobulbaceae	1
Proteobacteria_Desulfuromonadaceae	1
Proteobacteria_Pseudomonadaceae	1
Spirochaetes_Spirochaetaceae	1
Tenericutes_Anaeroplasmataceae	1

Here we see again that Prevotellaceae, Lachnospiraceae and Ruminococcaceae to have genera that are the significantly differentially abundant.

Phyla with Significant ASVs
Phylum	#Significant ASVs	Total ASVs	Percent Significant ASVs
Actinobacteria	23	96	23.958333
Bacteroidetes	56	1257	4.455052
Chloroflexi	15	39	38.461539
Cyanobacteria	6	65	9.230769
Elusimicrobia	3	16	18.750000
Euryarchaeota	16	44	36.363636
Fibrobacteres	8	39	20.512821
Firmicutes	540	3095	17.447496
Kiritimatiellaeota	17	180	9.444444
Lentisphaerae	3	31	9.677419
Patescibacteria	3	14	21.428571
Proteobacteria	11	219	5.022831
Spirochaetes	8	138	5.797101
Tenericutes	15	188	7.978723
Verrucomicrobia	1	35	2.857143
Deferribacteres	0	1	0.000000
Epsilonbacteraeota	0	2	0.000000
Fusobacteria	0	4	0.000000
Gemmatimonadetes	0	1	0.000000
Planctomycetes	0	15	0.000000
Synergistetes	0	6	0.000000

We also saw on the DPCoA that a group of Bacteroidetes (Prevotellaceae) was associated with the liquid strained samples. Additionally, another family in the same phylum, Lachnospiraceae, wasn’t associate with liquid strained samples.

As a reminder we can do differential abundance testing on genera and graph all the results from the phylum Bacteroidetes.

We will look further into these families to decipher what genera are causing this difference between grab and liquid samples.

## 
## -1  1 
##  2  4

In the family Prevotellaceae there are 2 genera significantly lower in relative abundance and 4 genera with significantly higher relative abundance in stomach tube compared to grab samples.

x	xmin	xmax	variable	Genus
-1.0395575	-1.4609369	-0.6181780	Liquid Strained Differential Abundance	Prevotellaceae_NK3B31_group
-0.6891250	-0.9859915	-0.3922586	Liquid Strained Differential Abundance	Prevotellaceae_UCG-004
0.8598287	0.7214513	0.9982061	Liquid Strained Differential Abundance	Prevotellaceae_UCG-001
1.1682901	0.2628093	2.0737709	Liquid Strained Differential Abundance	Prevotellaceae_YAB2003_group
1.1737147	1.0347963	1.3126331	Liquid Strained Differential Abundance	Prevotellaceae_UCG-003
1.2715117	1.0897500	1.4532734	Liquid Strained Differential Abundance	Prevotella_1

These are the Prevotellaceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.

## 
## -1  1 
##  7  8

In the family Ruminococcaceae there are 7 genera significantly lower in relative abundance and 8 genera with significantly higher relative abundance in stomach tube compared to grab samples.

x	xmin	xmax	variable	Genus
-1.3453328	-2.6413920	-0.0492735	Liquid Strained Differential Abundance	Caproiciproducens
-1.2056047	-1.3647354	-1.0464741	Liquid Strained Differential Abundance	Saccharofermentans
-0.8534209	-1.1680016	-0.5388402	Liquid Strained Differential Abundance	Papillibacter
-0.4246426	-0.5459944	-0.3032907	Liquid Strained Differential Abundance	Ruminococcus_1
-0.3820756	-0.5860149	-0.1781363	Liquid Strained Differential Abundance	Ruminococcaceae_UCG-005
-0.2635253	-0.4265474	-0.1005032	Liquid Strained Differential Abundance	Ruminococcaceae_UCG-010
-0.2426040	-0.3496181	-0.1355899	Liquid Strained Differential Abundance	Ruminococcaceae_UCG-014
0.2581495	0.1321582	0.3841409	Liquid Strained Differential Abundance	Ruminococcaceae_NK4A214_group
0.3558794	0.1207070	0.5910518	Liquid Strained Differential Abundance	Ruminococcus_2
0.5051468	0.2751281	0.7351655	Liquid Strained Differential Abundance	Ruminococcaceae_UCG-004
0.6982247	0.1210530	1.2753963	Liquid Strained Differential Abundance	Ruminococcaceae_UCG-001
0.8095391	0.4188809	1.2001974	Liquid Strained Differential Abundance	Ruminiclostridium_9
1.2720314	1.0289351	1.5151278	Liquid Strained Differential Abundance	Ruminococcaceae_V9D2013_group
1.6229601	1.2512347	1.9946856	Liquid Strained Differential Abundance	Ruminococcaceae_UCG-013
1.7220503	1.3963081	2.0477924	Liquid Strained Differential Abundance	Ruminococcaceae_UCG-002

These are the Ruminococcaceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.

## 
## -1  1 
## 22  3

In the family Lachnospiraceae there are 22 genera significantly lower in relative abundance and 3 genera with significantly higher relative abundance in stomach tube compared to grab samples.

x	xmin	xmax	variable	Genus
-1.6853162	-2.8561358	-0.5144965	Liquid Strained Differential Abundance	Butyrivibrio
-1.5519291	-1.8484651	-1.2553931	Liquid Strained Differential Abundance	Lachnoclostridium_10
-1.3151462	-2.3454300	-0.2848623	Liquid Strained Differential Abundance	Fusicatenibacter
-1.2927867	-1.7671418	-0.8184316	Liquid Strained Differential Abundance	Coprococcus_1
-1.2642825	-1.7307755	-0.7977896	Liquid Strained Differential Abundance	Lachnospiraceae_UCG-002
-1.2205535	-2.2914813	-0.1496256	Liquid Strained Differential Abundance	Lachnoclostridium
-1.1866044	-1.4115176	-0.9616912	Liquid Strained Differential Abundance	probable_genus_10
-1.1721461	-2.0657393	-0.2785528	Liquid Strained Differential Abundance	GCA-900066575
-1.1635327	-1.4643447	-0.8627207	Liquid Strained Differential Abundance	Lachnospiraceae_UCG-006
-1.1167935	-1.3105063	-0.9230807	Liquid Strained Differential Abundance	Lachnospiraceae_NK3A20_group
-1.1059423	-1.7519892	-0.4598953	Liquid Strained Differential Abundance	Lachnospiraceae_UCG-010
-1.0858461	-1.3568485	-0.8148437	Liquid Strained Differential Abundance	Marvinbryantia
-1.0489392	-1.3258423	-0.7720361	Liquid Strained Differential Abundance	Lachnospiraceae_FCS020_group
-0.9668531	-1.2363998	-0.6973064	Liquid Strained Differential Abundance	Moryella
-0.9563162	-1.6386116	-0.2740208	Liquid Strained Differential Abundance	Lachnospiraceae_FE2018_group
-0.9413635	-1.4029512	-0.4797758	Liquid Strained Differential Abundance	Acetatifactor
-0.9388259	-1.0801695	-0.7974823	Liquid Strained Differential Abundance	Lachnospiraceae_AC2044_group
-0.8050490	-1.0692876	-0.5408105	Liquid Strained Differential Abundance	Lachnospiraceae_UCG-008
-0.4973641	-0.8497914	-0.1449368	Liquid Strained Differential Abundance	possible_genus_Sk018
-0.4958562	-0.6231301	-0.3685824	Liquid Strained Differential Abundance	Butyrivibrio_2
-0.4777957	-0.6777349	-0.2778565	Liquid Strained Differential Abundance	Lachnospiraceae_XPB1014_group
-0.4617096	-0.6778755	-0.2455438	Liquid Strained Differential Abundance	Lachnospiraceae_ND3007_group
0.4937215	0.1923139	0.7951290	Liquid Strained Differential Abundance	Roseburia
0.7951294	0.3027545	1.2875042	Liquid Strained Differential Abundance	Tyzzerella_3
1.8744033	1.2078136	2.5409931	Liquid Strained Differential Abundance	Howardella

These are the Lachnospiraceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.

Stomach Tube vs Liquid Samples

## [1] "Families in liquid strained samples not in stomach tube"

##  [1] "Incertae_Sedis"     "Terrisporobacter"   "Breznakia"         
##  [4] "Allobaculum"        "Jeotgalicoccus"     "Proteiniclasticum" 
##  [7] "Sarcina"            "Gilvimarinus"       "Pigmentiphaga"     
## [10] "Aestuariispira"     "Methanimicrococcus" "Rhodobacter"       
## [13] "Ketogulonicigenium" "Sphingobium"        "Aureimonas"        
## [16] "Pseudochrobactrum"  "Glutamicibacter"    "Pontibacter"       
## [19] "Sphingobacterium"   "Anaerocella"        "Dyadobacter"       
## [22] "Anaerofilum"        "UBA1819"            "Faecalibacterium"  
## [25] "Oscillibacter"

## [1] "Families in stomach tube samples not in liquid strained samples"

##  [1] "Tyzzerella"               "Cellulosilyticum"        
##  [3] "Filifactor"               "Parvimonas"              
##  [5] "Kandleria"                "Desemzia"                
##  [7] "Alysiella"                "Limnohabitans"           
##  [9] "Leptotrichia"             "Salana"                  
## [11] "Curtobacterium"           "Leucobacter"             
## [13] "Harryflintia"             "Hydrogenoanaerobacterium"

## [1] "Families in liquid unstrained samples not in stomach tube"

##  [1] "Incertae_Sedis"    "Terrisporobacter"  "Paeniclostridium" 
##  [4] "Allobaculum"       "Jeotgalicoccus"    "Peptococcus"      
##  [7] "Proteiniclasticum" "Sarcina"           "Rhodobacter"      
## [10] "Pseudochrobactrum" "GWE2-31-10"        "Kineococcus"      
## [13] "Aeriscardovia"     "Glutamicibacter"   "Sphingobacterium" 
## [16] "Anaerocella"       "Chryseobacterium"  "Gillisia"         
## [19] "Rikenella"         "Dyadobacter"       "Hymenobacter"     
## [22] "Proteiniphilum"    "Negativibacillus"  "Oscillibacter"

## [1] "Families in stomach tube samples not in liquid unstrained samples"

##  [1] "Dorea"            "Filifactor"       "Parvimonas"      
##  [4] "Kandleria"        "Desemzia"         "Jeotgalibaca"    
##  [7] "Aeribacillus"     "Alysiella"        "Caviibacter"     
## [10] "Leptotrichia"     "Ochrobactrum"     "Salana"          
## [13] "Clavibacter"      "Frigoribacterium" "Leucobacter"     
## [16] "Aeromicrobium"    "Slackia"          "Synergistes"     
## [19] "Tannerella"       "Harryflintia"

Looking to see if stomach tubes are much different than liquid samples

Exploratory analysis of DPCoA.

This looks like liquid samples (strained mostly) differ from stomach tube samples in due to increases in Rikenellaceae, Prevotellaceae and Kiritimatiellaeota. Stomach stube samples have an increase in Christensenllaceae and Lachnospiraceae.

Depeters Study 2018

Jill Hagey

Started: 10/5/18, Completed: 9/XX/2020

Research questions

We seek to answer the following questions:

Other Questions of interest:

Running DADA2 to get ASVs and assign taxonomy.

Making phyloseq object

Cleaning data

More cleaning of data

Looking at metrics after filtering

Rechecking read stats

Abundance of Phyla

Abundance of families

Archaea Populations

Unsupervised exploratory analysis

Shared ASVs between sample types.

Differential Abundance Testing

Corncob: Grab sample vs all other sample types

Alpha Diversity

Richness

Evenness

Beta Diversity

Grab vs fecal samples

Corncob

Grab Samples vs other rumen samples

Metrics after filtering

Exploratory Analysis

Transfaunating what communites?

Communites found in stomach tube samples

Grab vs stomach tube samples

Grab vs liquid strained samples

Stomach Tube vs Liquid Samples